Dissertations / Theses: '3D brain imaging'

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Matias, Correia T. M. "Assessment and optimisation of 3D optical topography for brain imaging." Thesis, University College London (University of London), 2010. http://discovery.ucl.ac.uk/19496/.

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Optical topography has recently evolved into a widespread research tool for non-invasively mapping blood flow and oxygenation changes in the adult and infant cortex. The work described in this thesis has focused on assessing the potential and limitations of this imaging technique, and developing means of obtaining images which are less artefactual and more quantitatively accurate. Due to the diffusive nature of biological tissue, the image reconstruction is an ill-posed problem, and typically under-determined, due to the limited number of optodes (sources and detectors). The problem must be regularised in order to provide meaningful solutions, and requires a regularisation parameter (\lambda), which has a large influence on the image quality. This work has focused on three-dimensional (3D) linear reconstruction using zero-order Tikhonov regularisation and analysis of different methods to select the regularisation parameter. The methods are summarised and applied to simulated data (deblurring problem) and experimental data obtained with the University College London (UCL) optical topography system. This thesis explores means of optimising the reconstruction algorithm to increase imaging performance by using spatially variant regularisation. The sensitivity and quantitative accuracy of the method is investigated using measurements on tissue-equivalent phantoms. Our optical topography system is based on continuous-wave (CW) measurements, and conventional image reconstruction methods cannot provide unique solutions, i.e., cannot separate tissue absorption and scattering simultaneously. Improved separation between absorption and scattering and between the contributions of different chromophores can be obtained by using multispectral image reconstruction. A method is proposed to select the optimal wavelength for optical topography based on the multispectral method that involves determining which wavelengths have overlapping sensitivities. Finally, we assess and validate the new three-dimensional imaging tools using in vivo measurements of evoked response in the infant brain.

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Law, Kwok-wai Albert, and 羅國偉. "3D reconstruction of coronary artery and brain tumor from 2D medical images." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B31245572.

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Uthama, Ashish. "3D spherical harmonic invariant features for sensitive and robust quantitative shape and function analysis in brain MRI." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/438.

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A novel framework for quantitative analysis of shape and function in magnetic resonance imaging (MRI) of the brain is proposed. First, an efficient method to compute invariant spherical harmonics (SPHARM) based feature representation for real valued 3D functions was developed. This method addressed previous limitations of obtaining unique feature representations using a radial transform. The scale, rotation and translation invariance of these features enables direct comparisons across subjects. This eliminates need for spatial normalization or manually placed landmarks required in most conventional methods [1-6], thereby simplifying the analysis procedure while avoiding potential errors due to misregistration. The proposed approach was tested on synthetic data to evaluate its improved sensitivity. Application on real clinical data showed that this method was able to detect clinically relevant shape changes in the thalami and brain ventricles of Parkinson's disease patients. This framework was then extended to generate functional features that characterize 3D spatial activation patterns within ROIs in functional magnetic resonance imaging (fMRI). To tackle the issue of intersubject structural variability while performing group studies in functional data, current state-of-the-art methods use spatial normalization techniques to warp the brain to a common atlas, a practice criticized for its accuracy and reliability, especially when pathological or aged brains are involved [7-11]. To circumvent these issues, a novel principal component subspace was developed to reduce the influence of anatomical variations on the functional features. Synthetic data tests demonstrate the improved sensitivity of this approach over the conventional normalization approach in the presence of intersubject variability. Furthermore, application to real fMRI data collected from Parkinson's disease patients revealed significant differences in patterns of activation in regions undetected by conventional means. This heightened sensitivity of the proposed features would be very beneficial in performing group analysis in functional data, since potential false negatives can significantly alter the medical inference. The proposed framework for reducing effects of intersubject anatomical variations is not limited to functional analysis and can be extended to any quantitative observation in ROIs such as diffusion anisotropy in diffusion tensor imaging (DTI), thus providing researchers with a robust alternative to the controversial normalization approach.

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Olivero, Daniel. "Traumatic brain injury biomarker discovery using mass spectrometry imaging of 3D neural cultures." Thesis, Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41102.

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Biomarker research is of great interest in the field of traumatic brain injury (TBI), since there are numerous potential markers that may indicate central nervous system damage, yet the brain is normally well isolated and discovery is at its infancy. Traditional methods for biomarker discovery include time consuming multi step chromatographic mass spectrometery (MS) techniques or pre-defined serial probing using traditional assays, making the identification of biomarker panels limiting and expensive. These shortfalls have motivated the development of a MS based probe that can be embedded into 3D neural cultures and obtain temporal and spatial information about the release of biomarkers. Using the high sensitivity MS ionization method of nano-electrospray ionization (nano-ESI) with an in-line microdialysis (MD) unit allows us to use MS to analyze low concentrations of TBI biomarkers from within cell cultures with no need for off-line sample manipulation. This thesis goes through the development of the probe by studying the theoretical principles, simulations and experimental results of the probe's capability to sample small local concentrations of a marker within cell culture matrix, the MD unit's sample manipulation capabilities, and the ability to detect markers using in-line MD-nano-ESI MS.

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MomayyezSiahkal, Parya. "3D stochastic completion fields for mapping brain connectivity using diffusion magnetic resonance imaging." Thesis, McGill University, 2012. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=110445.

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This thesis proposes a novel probabilistic method for measuring anatomical connectivity in the brain based on measurements obtained from diffusion magnetic resonance imaging. We approach the problem of fibre tractography from the viewpoint that a computational theory should relate to the underlying quantity that is being measured--the anisotropic diffusion of water molecules in fibrous tissues. To achieve this goal, the prior probability of completion between two particular regions of interest is modelled by a 3D directional random walk, which is representative of the ensemble anisotropic displacement to which diffusion-MRI measurements have been sensitized. The 3D directional random walk is controlled by a set of stochastic differential equations whose solution provides the probability of passing through every state in space given initial source and sink regions. Under such a model, particles tend to travel in a straight line, with a slight perturbation in their 3D orientation at each step governed by two consecutive Brownian motions in the spherical components of the orientation. The probability density functions describing the likelihood of passing through a particular position and orientation in 3D, given an initial source region and a final sink region, are respectively called a stochastic source field and a stochastic sink field. The final stochastic completion field is estimated by the product of these two densities and it represents the probability of passing through a particular state in space, while bridging the gap between the two regions. We show that the maximum likelihood curves obtained under the 3D directional random walk are curves of least energy which minimize a weighted sum of curvature squared, torsion squared and length. The 3D directional random walk and the associated completion fields are an extension of Williams and Jacobs' 2D completion model for curve completion in the plane. We then develop an efficient, local and parallelizable computational method to obtain the stochastic completion fields by exploiting the Fokker-Planck equation of the 3D directional random walk. This partial differential equation describes the evolution of the probability distribution of particles following such a random process. Additionally, a rotation invariant solution is proposed using a spherical harmonics basis to capture directions on the 2-sphere. In analogy with the 2D model of completion, we introduce additional diffusion terms to make spatial advection errors isotropic. The 3D stochastic completion field is further adapted to those problems where dense orientation data is present, as is the case for diffusion MRI measurements. The insertion of angular drift terms into the overall stochastic process provides a principled way to compute completions, while exploiting the local orientation information available at each voxel in the volume. Our algorithm provides a novel index of connectivity between two regions of interest, which is based on the overall probability for the computed completion curves between the two. We then discuss an alternative model of the directional random walk, where the 3D orientation change is drawn from a single distribution, i.e., a 3D Brownian distribution.The performance of the stochastic completion field algorithm is validated qualitatively and quantitatively on diffusion-MRI data from biological phantoms and on synthetic data. In vivo human data from 12 subjects is then used to investigate the algorithm's performance qualitatively by comparing the output of our method with published results based on another tractography method. Finally, we conclude by discussing the advantages and limitations of the method developed in this thesis and suggest directions for future work. Cette thèse propose un nouveau cadre probabiliste pour la reconstruction de la connectivité anatomique dans le cerveau basée sur les données obtenues avec l'imagerie de diffusion par résonance magnétique. Nous abordons le problème de la tractographie par le point de vue qu'une théorie basée sur des calculs numériques doit se rapporter à la quantité sous jacente qui est mesurée-la diffusion anisotropique des molécules d'eau. Pour atteindre cet objectif, la probabilité de complétion à priori entre deux régions d'intérêt est modélisée par une marche aléatoire tridimensionnelle (3D), représentative du déplacement anisotropique local capturé par l'IRM de diffusion. La marche aléatoire 3D varie selon un ensemble d'équations différentielles stochastiques dont la solution fournit la probabilité de passage entre tous les états dans l'espace, étant donné une source initiale et des régions d'intérêts. Dans un tel modèle, les particules ont tendance à se diriger en ligne droite à chaque passage, avec une légère perturbation dans leur orientation tridimensionnelle provenant de mouvement Brownien dans chaque composante de l'orientation. Étant données initialement une région source et une région finale, les fonctions de densité de probabilité décrivant la vraisemblance de passage par une position et orientation tridimensionnelle sont respectivement nommées champ stochastique source et champ stochastique d'intérêt. Le champ stochastique final est estimé par le produit de ces deux densités et représente la probabilité de passage par un état particulier dans l'espace. Nous montrons que les courbes de maximum de vraisemblance obtenues par le procédé de marche aléatoire directionnelle 3D est la courbe de moindre énergie qui minimise la somme pondérée de la courbature au carrée, de la torsion au carrée et de la longueur. La marche aléatoire directionnelle 3D et ses champ de complétion sont une extension du modèle de complétion de Williams et Jacobs pour la complétion 2D.Nous développons ensuite un modèle de calcul efficace, local et parallellisable pour calculer les champs de complétion stochastiques en exploitant l'équation Fokker-Planck de la marche aléatoire directionnelle 3D. Cette équation différentielle partielle décrit l'évolution de la distribution de probabilité pour les particules de suivre un tel processus aléatoire. De plus, une solution invariante par rotation est proposée en utilisant la base des fonctions harmoniques sphériques afin de capturer la direction sur la sphere. En analogie avec le modèle de complétion 2D, nous introduisions des termes de diffusion additionnels pour rendre les erreurs d'advection spatiales isotropiques. Le champ de complétion stochastique 3D est également adapté plus avant lorsque les données d'orientation sont dense, comme c'est le cas pour l'IRM de diffusion. L'insertion de termes de dérive angulaire dans le processus stochastique global fournit un moyen de calculer les complétions tout en exploitant les informations locales d'orientation accessibles dans chaque voxel. Notre algorithme fournit ainsi une nouvelle mesure de la connectivité entre deux régions d'intérêt en se basant sur la probabilité globale des courbes de complétions entre elles. Nous discutions ensuite d'un modèle alternatif de marche directionnelle aléatoire directionnelle, où la perturbation angulaire provient d'une seule distribution, i.e., une distribution 3D brownienne.Les performances de l'algorithme de champ de complétion sont validées qualitativement et quantitativement sur des données d'IRM de diffusion provenant de fantômes synthétiques et biologiques. Les données humaines acquises in vivo sur 12 patients sont utilisées pour comparer les performances de l'algorithme que nous proposons avec d'autres méthodes de tractographie de l'état de l'art. Nous concluons finalement par une discussion sur les avantages et les limitations de la méthode développée dans cette thèse et suggérons des orientations pour les travaux futurs.

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Collins, D. Louis. "3D model-based segmentation of individual brain structures from magnetic resonance imaging data." Thesis, McGill University, 1994. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=28716.

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This thesis addresses a specific problem of model-based segmentation; namely, the automatic identification and delineation of gross anatomical structures of the human brain based on their appearance in magnetic resonance images (MRI). The approach developed in this thesis depends on a general, iterative, hierarchical registration procedure and a 3-D digital model of human brain anatomy that contains both volumetric intensity-based data and geometric atlas data that co-exist in a brain-based stereotaxic coordinate system. The model contains features derived from an MRI atlas of gross neuroanatomy, that is the result of an intensity average of 305 brains created with an automatic stereotaxic registration procedure developed here. The objective of this thesis is achieved by inverting the traditional segmentation strategy. Instead of matching geometric contours from an idealized atlas directly to the MRI data, segmentation is achieved by identifying the spatial transformation that, under certain constraints, best maps corresponding features between the model and a particular volumetric data set. After automatic recovery of the linear registration transform, the 3-D non-linear transformation is recovered by estimating the local deformation fields, recursively selected by stepping through the entire target volume in a 3D grid pattern, using cross-correlation of invariant intensity features derived from image data. This registration process is performed hierarchically, with each step in decreasing scale refining the fit of the previous step and providing input to the next. When completed, atlas contours defined in the model are mapped through the recovered transformation to segment structures in the original data set and identify them by name. Experiments for registration and segmentation are presented using simple phantoms, a realistic digital brain phantom as well as human MRI data. The algorithm is used to estimate neuro-anatomical variability, to automatically segment cerebral structures and to create probabilistic representations of the same structures. Validation with manual methods shows that the procedure performs well, is objective and its implementation robust.

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Christopoulos, Charitos Andreas. "Brain disease classification using multi-channel 3D convolutional neural networks." Thesis, Linköpings universitet, Statistik och maskininlärning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-174329.

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Functional magnetic resonance imaging (fMRI) technology has been used in the investigation of human brain functionality and assist in brain disease diagnosis. While fMRI can be used to model both spatial and temporal brain functionality, the analysis of the fMRI images and the discovery of patterns for certain brain diseases is still a challenging task in medical imaging. Deep learning has been used more and more in medical field in an effort to further improve disease diagnosis due to its effectiveness in discovering high-level features in images. Convolutional neural networks (CNNs) is a class of deep learning algorithm that have been successfully used in medical imaging and extract spatial hierarchical features. The application of CNNs in fMRI and the extraction of brain functional patterns is an open field for research. This project focuses on how fMRIs can be used to improve Autism Spectrum Disorders (ASD) detection and diagnosis with 3D resting-state functional MRI (rs-fMRI) images. ASDs are a range of neurodevelopment brain diseases that mostly affect social function. Some of the symptoms include social and communicating difficulties, and also restricted and repetitive behaviors. The symptoms appear on early childhood and tend to develop in time thus an early diagnosis is required. Finding a proper model for identifying between ASD and healthy subject is a challenging task and involves a lot of hyper-parameter tuning. In this project a grid search approach is followed in the quest of the optimal CNN architecture. Additionally, regularization and augmentation techniques are implemented in an effort to further improve the models performance.

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Mayerich, David Matthew. "Acquisition and reconstruction of brain tissue using knife-edge scanning microscopy." Texas A&M University, 2003. http://hdl.handle.net/1969.1/563.

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A fast method for gathering large-scale data sets through the serial sectioning of brain tissue is described. These data sets are retrieved using knife-edge scanning microscopy, a new technique developed in the Brain Networks Laboratory at Texas A&M University. This technique allows the imaging of tissue as it is cut by an ultramicrotome. In this thesis the development of a knife-edge scanner is discussed as well as the scanning techniques used to retrieve high-resolution data sets. Problems in knife-edge scanning microscopy, such as illumination, knife chatter, and focusing are discussed. Techniques are also shown to reduce these problems so that serial sections of tissue can be sampled at resolutions that are high enough to allow reconstruction of neurons at the cellular level.

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Heinzer, Stefan. "Hierarchical 3D imaging and quantification of brain microvasculature in a mouse model for Alzheimer's disease /." Zürich : ETH, 2007. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=17293.

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Nguyen, Peter. "CANNABINOID RECEPTORS IN THE 3D RECONSTRUCTED MOUSE BRAIN: FUNCTION AND REGULATION." VCU Scholars Compass, 2010. http://scholarscompass.vcu.edu/etd/2274.

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CB1 receptors (CB1R) mediate the psychoactive and therapeutic effects of cannabinoids including ∆9-tetrahydrocannabinol (THC), the main psychoactive constituent in marijuana. However, therapeutic use is limited by side effects and tolerance and dependence with chronic administration. Tolerance to cannabinoid-mediated effects is associated with CB1R adaptations, including desensitization (receptor-G-protein uncoupling) and downregulation (receptor degradation). The objectives of this thesis are to investigate the regional-specificity in CB1R function and regulation. Previous studies have investigated CB1Rs in a subset of regions involved in cannabinoid effects, but an inclusive regional comparison of the relative efficacies of different classes of cannabinoids to activate G-proteins has not been conducted. A novel unbiased whole-brain analysis was developed based on Statistical Parametric Mapping (SPM) for 3D-reconstructed mouse brain images derived from agonist-stimulated [35S]GTPgS autoradiography, which has not been described before. SPM demonstrated regional differences in the relative efficacies of cannabinoid agonists methanandamide (M-AEA), CP55,940 (CP), and WIN55,212-2 (WIN) in mouse brains. To assess potential contribution of novel sites, CB1R knockout (KO) mice were used. SPM analysis revealed that WIN, but not CP or M-AEA, stimulated [35S]GTPgS binding in regions that partially overlapped with the expression of CB1Rs. We then examined the role of the regulatory protein Beta-arrestin-2 (βarr2) in CB1R adaptations to chronic THC treatment. Deletion of βarr2 reduced CB1R desensitization/downregulation in the cerebellum, caudal periaqueductal gray (PAG), and spinal cord. However in hippocampus, amygdala and rostral PAG, similar desensitization was present in both genotypes. Interestingly, enhanced desensitization was found in the hypothalamus and cortex in βarr2 KO animals. Intra-regional differences in the magnitude of desensitization were noted in the caudal hippocampus, where βarr2 KO animals exhibited greater desensitization compared to WT. Regional differences in βarr2-mediated CB1R adaptation were associated with differential effects on tolerance, where THC-mediated antinociception, but not catalepsy or hypothermia, was attenuated in βarr2 KO mice. Overall, studies using SPM revealed intra- and inter-regional specificity in the function and regulation of CB1Rs and underscores an advantage of using a whole-brain unbiased approach. Understanding the regulation of CB1R signaling within different anatomical contexts represents an important fundamental prerequisite in the therapeutic exploitation of the cannabinoid system.

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Rambani, Komal. "Thick brain slice cultures and a custom-fabricated multiphoton imaging system: progress towards development of a 3D hybrot model." Thesis, Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/22702.

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Development of a three dimensional (3D) HYBROT model with targeted in vivo like intact cellular circuitry in thick brain slices for multi-site stimulation and recording will provide a useful in vitro model to study neuronal dynamics at network level. In order to make this in vitro model feasible, we need to develop several associated technologies. These technologies include development of a thick organotypic brain slice culturing method, a three dimensional (3D) micro-fluidic multielectrode Neural Interface system (ÂµNIS) and the associated electronic interfaces for stimulation and recording of/from tissue, development of targeted stimulation patterns for closed-loop interaction with a robotic body, and a deep-tissue non-invasive imaging system. To make progress towards this goal, I undertook two projects: (i) to develop a method to culture thick organotypic brain slices, and (ii) construct a multiphoton imaging system that allows long-term and deep-tissue imaging of two dimensional and three dimensional cultures. Organotypic brain slices preserve cytoarchitecture of the brain. Therefore, they make more a realistic reduced model for various network level investigations. However, current culturing methods are not successful for culturing thick brain slices due to limited supply of nutrients and oxygen to inner layers of the culture. We developed a forced-convection based perfusion method to culture viable 700Âµm thick brain slices. Multiphoton microscopy is ideal for imaging living 2D or 3D cultures at submicron resolution. We successfully fabricated a custom-designed high efficiency multiphoton microscope that has the desired flexibility to perform experiments using multiple technologies simultaneously. This microscope was used successfully for 3D and time-lapse imaging. Together these projects have contributed towards the progress of development of a 3D HYBROT. ----- 3D Hybrot: A hybrid system of a brain slice culture embodied with a robotic body.

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D'Souza, Aswin Cletus. "Automated counting of cell bodies using Nissl stained cross-sectional images." [College Station, Tex. : Texas A&M University, 2007. http://hdl.handle.net/1969.1/ETD-TAMU-2035.

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Li, Fan. "Segmentation and Symbolic Representation of Brain Vascular Network : Application to ArterioVenous Malformations." Thesis, Paris Est, 2016. http://www.theses.fr/2016PESC1048/document.

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Le traitement et l’analyse d’images angiographiques rotationnelles 3D (3DRA) de haute résolution spatiale pour l’aide à la planification d’interventions en neuroradiologie interventionnelle est un domaine de recherche récent et en plein essor. Les neuroradiologues ont besoin d’outils interactifs pour la planification des procédures d’embolisation et l’optimisation du guidage de microcathéters durant les interventions endovasculaires. L’exploitation des données d’imagerie pour l’aide au diagnostic et la thérapeutique requiert le développement d’algorithmes robustes et de méthodes efficaces. Ces méthodes permettent d’intégrer les informations contenues dans ces images pour en extraire des descripteurs anatomiques utiles durant les phases pre et per-opératoires.Cette thèse est dédiée au développement d’une chaine de traitement complète comprenant la segmentation, la reconstruction tridimensionnelle (3D) et la représentation symbolique de vaisseaux cérébraux à partir d’images 3DRA, pour faciliter la planification d’interventions d’embolisation pour le traitement de Malformations ArtérioVeineuses cérébrales (MAVs).La première partie du travail est consacrée à l’étude des différentes approches utilisées en segmentation des vaisseaux. Deux méthodes de segmentation sont ensuite proposées. Tout d’abord, une méthode de segmentation 2D coupe par coupe est développée ainsi qu’un technique robuste de suivi de vaisseaux permettant de détecter les bifurcations et de poursuivre le tracking de plusieurs branches du même vaisseau. Un maillage basé sur la triangulation Contrainte de Delaunay permet ensuite la reconstruction et la visualisation 3D des vaisseaux ainsi obtenus. Une méthode de segmentation 3D automatisée des images 3DRA est ensuite développée, elle présente l’avantage d’être plus rapide et de traiter le volume d’images entier en 3D. Cette méthode est basée sur la croissance de régions. Le processus 3D démarre à partir d’une coupe initiale pré-segmentée en utilisant la reconstruction géodésique et sur laquelle les germes sont placés de manière automatique. Finalement, une représentation du réseau vasculaire sur laquelle on distingue clairement les trois entités que sont les artères, les veines drainantes et le nidus est obtenue.La deuxième partie de la thèse est consacrée à la représentation symbolique des vaisseaux. L'étude hiérarchique du squelette permet de donner une description graphique du réseau vasculaire cérébral. A partir de cette description graphique, les vaisseaux et leurs branches sont labellisés et un ou plusieurs vaisseaux peuvent être isolés du reste du réseau pour une analyse visuelle plus précise, ce qui n’est pas possible avec les reconstructions 3D du constructeur. De plus, cette représentation améliore la détermination des chemins optimaux pour l’embolisation de la MAV et réduit la complexité due à l’enchevêtrement des vaisseaux malformés.La chaine de traitement complète ainsi développée aboutit à une description 3D précise des vaisseaux. Elle permet une meilleure compréhension structurelle du réseau vasculaire cérébral et offre aux neuroradiologues la possibilité d’extraire des descripteurs anatomiques, et géométriques (taille, diamètre…) des vaisseaux. Enfin, une étape de vérification des résultats par un expert neuroradiologue a permis la validation clinique des résultats de segmentation et de reconstruction 3D. L’intégration des algorithmes développés dans une interface graphique intuitive et facile d’utilisation devra être faite pour permettre l’exploitation de nos résultats en routine clinique The processing and analysis of 3D Rotational Angiographic images (3DRA) of high spatial resolution to facilitate intervention planning in interventional neuroradiology is a new and booming research area. Neuroradiologists need interactive tools for the planning of embolization procedures and the optimization of the guidance of micro-catheters during endovascular interventions. The exploitation of imaging data to help in diagnosis and treatment requires the development of robust algorithms and efficient methods. These methods allow integrating information included in these images in order to extract useful anatomical descriptors during preoperative and peroperative phases.This thesis is dedicated to the development of a complete processing pipeline including segmentation, three-dimensional (3D) reconstruction and symbolic representation of cerebral vessels from 3DRA images, aiming to facilitate the embolization intervention planning for the treatment of cerebral ArterioVenous Malformations (AVMs).The first part of the work is devoted to the study of the different approaches used for the segmentation of vessels. Two segmentation methods are then proposed. First, a 2D slice-by-slice segmentation method is developed, followed by a robust vessel tracking process that enables detecting bifurcations and further following several branches of the same vessel. A mesh based on the Constrained Delaunay triangulation allows then the 3D reconstruction and visualization of the obtained vessels. An automated 3D segmentation method of 3DRA images is then developed, which presents the advantage of being faster and processing the whole 3D volume of images. This method is region growing based. The 3D process starts from an initial pre-segmented slice using the geodesic reconstruction, where the seeds are automatically placed. Finally, a representation of the vasculature is obtained, in which these three entities are clearly visible: the feeding arteries, the draining veins and the nidus.The second part of the thesis is devoted to the symbolic representation of the vessels. The hierarchical study of the skeleton allows giving a graphic description of the cerebral vascular network. From this graphic description, the vessels and their branches are labeled and one or more vessels can be isolated from the rest of network for a more accurate visual analysis, which is not possible with the original 3D reconstructions. Moreover, this improves the determination of the optimal paths for the AVM embolization and reduces the complexity due to the entanglement of the malformed vessels.The complete processing pipeline thus developed leads to a precise 3D description of the vessels. It allows a better understanding of the cerebral vascular network structure and provides the possibility to neuroradiologists of extracting anatomical and geometric descriptors (size, diameter...) of the vessels. Finally, a verification step of the results by a neuroradiology expert enabled clinical validation of the 3D segmentation and reconstruction results. The integration of the developed algorithms in a user-friendly graphical interface should be achieved to allow the exploitation of our results in clinical routine

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KAWAI, HISASHI, KIMINORI BOKURA, SHINJI NAGANAWA, and MASAHIRO YAMAZAKI. "VISUALIZATION OF BRAIN WHITE MATTER TRACTS USING HEAVILY T2-WEIGHTED THREE-DIMENSIONAL FLUID-ATTENUATED INVERSION-RECOVERY MAGNETIC RESONANCE IMAGING." Nagoya University School of Medicine, 2014. http://hdl.handle.net/2237/20547.

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Walker, Matthew David. "Quantitative dynamic 3D PET scanning of the body and brain using LSO tomographs." Thesis, University of Manchester, 2009. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:78135.

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Castelli, Filippo Maria. "3D CNN methods in biomedical image segmentation." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18796/.

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A definite trend in Biomedical Imaging is the one towards the integration of increasingly complex interpretative layers to the pure data acquisition process. One of the most interesting and looked-forward goals in the field is the automatic segmentation of objects of interest in extensive acquisition data, target that would allow Biomedical Imaging to look beyond its use as a purely assistive tool to become a cornerstone in ambitious large-scale challenges like the extensive quantitative study of the Human Brain. In 2019 Convolutional Neural Networks represent the state of the art in Biomedical Image segmentation and scientific interests from a variety of fields, spacing from automotive to natural resource exploration, converge to their development. While most of the applications of CNNs are focused on single-image segmentation, biomedical image data -being it MRI, CT-scans, Microscopy, etc- often benefits from three-dimensional volumetric expression. This work explores a reformulation of the CNN segmentation problem that is native to the 3D nature of the data, with particular interest to the applications to Fluorescence Microscopy volumetric data produced at the European Laboratories for Nonlinear Spectroscopy in the context of two different large international human brain study projects: the Human Brain Project and the White House BRAIN Initiative.

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Gibert, Guillaume. "Quantification of the Cerebral Perfusion with the Arterial Spin Labelling 3D-MRI method. Quantification of the Cerebral Perfusion with the Arterial Spin Labelling 3D-MRI method." Thesis, KTH, Skolan för teknik och hälsa (STH), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-148020.

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The Arterial Spin Labelling (ASL) method is a Magnetic Resonance technique used toquantify the cerebral perfusion. It has the big advantage to be non-invasive so doesn’tneed the injection of any contrast agent. But due to a relatively low Signal-to-NoiseRatio (SNR) of the signal acquired (only approximately 1% of the image intensity), ithas been hampered to be widely used in a clinical setting so far.The primary objective of this project is to make the method more robust by improvingthe quality of the images, the SNR, and by reducing the acquisition time. DifferentASL protocols with different sets of parameters have been investigated. The modificationsperformed on the protocol have been investigated by analyzing images acquired onhealthy volunteers. An optimized protocol leading to a good trade-off between the differentaspects of the method, has been suggested. It is characterized by a 3:43:44:0mm3with a two-segment acquisition.A more advanced ASL method implies the acquisition of images at different inversiontimes (TI), which is called the mutli-TI method. The influence of the range of TI used inthe method has been explored. An optimized TI range (from 410ms to 3860ms, sampledevery 150ms) has been suggested to make the ASL method as performant as possible.A numerical model and a fitting algorithm have been used to extract the informationon the perfusion from the images acquired. Different models have been investigated aswell as their influence on the reliability of the results.Finally, a criterion has been implemented to evaluate the reliability of the results sothat the clinician or the user of the method can figure out how much he can count onthe results provided by the method.

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Dohmen, Melanie [Verfasser]. "Towards the Reconstruction of Fiber Tracts in the Human Brain by Means of 3D Polarized Light Imaging / Melanie Dohmen." Wuppertal : Universitätsbibliothek Wuppertal, 2013. http://d-nb.info/1045118958/34.

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Frost, Stephen Robert. "Diffusion-weighted magnetic resonance imaging with readout-segmented echo-planar imaging." Thesis, University of Oxford, 2012. https://ora.ox.ac.uk/objects/uuid:94421cdc-6bcb-49c2-b9d9-64e016b875f8.

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Diffusion-weighted (DW) magnetic resonance imaging is an important neuroimaging technique that has successful applications in diagnosis of ischemic stroke and methods based on diffusion tensor imaging (DTI). Tensor measures have been used for detecting changes in tissue microstructure and for non-invasively tracing white matter connections in vivo. The most common image acquistion strategy is to use a DW single-shot echo-planar imaging (ss-EPI) pulse sequence, which is attractive due to its robustness to motion artefacts and high imaging speed. However, this sequence has limited achievable spatial resolution and suffers from geometric distortion and blurring artefacts. Readout-segmented echo-planar imaging (rs-EPI) is a DW sequence that is capable of acquiring high-resolution images by segmenting the acquisition of k- space into multiple shots. The fast, short readouts reduce distortion and blurring and the problem of artefacts due to motion-induced phase changes between shots can be overcome with navigator techniques. The rs-EPI sequence has two main shortcomings. (i) The method is slow to produce image volumes, which is limiting for clinical scans due to patient welfare and prevents us from acquiring very many directions in DTI. (ii) The sequence (like other diffusion techniques) is far from the optimum repetition time (TR) for acquiring data with the highest possible signal-to-noise ratio (SNR) in a given time. The work in this thesis seeks to address both of these important issues using a range of approaches. In Chapter 4 a partial Fourier extension is presented, which addresses point (i) by reducing the number of readout segments acquired and estimating the missing data. This allows reductions in scan time by approximately 40&percnt; and the reliability of the images is demonstrated in comparisons with the original images. The application of a simultaneous multi-slice scheme to rs-EPI, to address points (i) and (ii), is described in Chapter 5. Using the slice-accelerated rs-EPI sequence, tractography data were compared to ss-EPI data and high-resolution trace-weighted data were acquired in clinically relevant scan times. Finally, a 3D multi-slab extension that addresses point (i) is presented in Chapter 6. A 3D sequence could also allow higher resolution in the slice direction than 2D multi-slice methods, which are limited by the difficulties in exciting thin, accurate slices. A 3D version of rs-EPI was simulated and implemented and a k-space acquisition synchronised to the cardiac cycle showed substantial improvements in image artefacts compared to a conventional k-space acquisition.

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Mercier, Corentin. "Geometrical modeling, simplification and visualization of brain white matter tractograms." Electronic Thesis or Diss., Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAT048.

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Les données de tractographie (fibres) obtenues à partir d'IRM de diffusion sont difficiles d'utilisation. Dans cette thèse, nous proposons des méthodes et algorithmes pour la simplification, la visualisation et la manipulation de ces données. Nous introduisons une représentation multi-résolution des tractogrammes, plus rapides et avec une meilleure précision géométrique que les approches de simplification existantes. Nous explorons aussi diverses représentations géométriques et nous nous concentrons sur les approches de projections aux moindres carrés (MLS) par l'intermédiaire des surfaces algébriques d'ensemble de points (APSS), pour lesquelles nous réduisons la complexité, permettant l'utilisation de noyaux globaux pour l'analyse et la modélisation. Une technique de segmentation utilisant la représentation multi-résolution et permettant une meilleure reproductibilité que d'autres approches est ensuite présentée. Les tractogrammes pouvant être volumineux, nous introduisons un algorithme de compression exploitant la manière d'obtenir les données à partir des IRM de diffusion. La vitesse de cet algorithme permet même son utilisation pour la visualisation de données compressées, la décompression se faisant à la volée sur le GPU. Ces travaux de recherche et les résultats obtenus se situent à l'intersection de l'informatique graphique et de l'analyse de données médicales, ouvrant de nombreuses perspectives Tractography data (fibers) obtained from diffusion MRI present several challenges.In this thesis, we propose some useful methods and algorithms for simplification, visualization, and manipulation of these data.We introduce a new multi-resolution representation for tractograms, faster, and with higher geometric accuracy than existing simplification approaches.We also investigate various geometric representations and focus on moving least square (MLS) projection with algebraic point set surfaces (APSS), on which we reduce the complexity, allowing for the use of global kernels for analysis and modeling.A segmentation technique using the multi-resolution representation is presented, achieving better reproducibility than other approaches.Tractograms being massive, we also introduce a compression algorithm taking advantage of data obtention from diffusion MRI.The algorithm speed even allows for the direct use of compressed data for visualization, as it can be decompressed on-the-fly on the GPU.This research and the obtained results lie at the intersection between Computer Graphics and Medical Data Analysis, paving the way for numerous perspectives

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Manganas, Spyridon. "A Novel Methodology for Timely Brain Formations of 3D Spatial Information with Application to Visually Impaired Navigation." Wright State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=wright1567452284983244.

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Morgan, Leah. "Development of a 3D radial MR Imaging sequence to be used for (self) navigation during the scanning of the fetal brain in utero." Master's thesis, University of Cape Town, 2016. http://hdl.handle.net/11427/22735.

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Imaging the fetal brain in utero is challenging due to the unpredictable motion of the fetus. Although ultra-fast MRI sequences are able to image a 2D slice in under a second, thus limiting the time in which fetal motion can corrupt images, Cartesian sampling makes these sequences sensitive to signal misregistration and motion-corruption. Corruption of a single 2D slice renders it impossible to reconstruct 3D volumes from these slices without complex slice-to-volume registration. There is a need for motion-robust sequences that can produce high-resolution 3D volumes of the fetal brain. The Siemens Cardiovascular sequence was edited to produce a new radial readout that sampled a 3D spherical volume of k-space with successive diametric spokes. The diameter end points map a spiral trajectory on the surface of a sphere. The trajectory was modified so that multiple sub-volumes of data are sampled during a single acquisition where M is the number of sub-spirals and N is the number of diametric spokes per sub-spiral. This allows reconstruction of individual sub-volumes of data to produce a series of low-resolution navigator images that can be co-registered to provide information on motion during the acquisition. In this way, a segmented sequence suited to self-navigation was developed. Imaging parameters for the 3D radial sequence were optimised based on theoretical calculations and scans performed in adult brains and abdomens. Optimum values for M and N needed to be determined. Increasing M for a constant total number of projections improves the temporal accuracy of motion tracking at the expense of decreased signal to noise ratio in the navigator images. The effects of breathing and rigid body motion on image quality were also compared between 3D radial and equivalent 3D Cartesian acquisitions. Custom reconstruction code was written to separate the incoming scan data according to the sub-spiral trajectories described within the sequence such that individual navigator images could be reconstructed. Successive sub-spiral images were co-registered to the first navigator image to quantify motion during the acquisition. The resulting transformation matrices were then applied to each sub-spiral image after reconstruction and co-registered sub-spiral images combined in image space to generate the final 3D volume. To improve the quality of navigator images, a method is presented to perform navigator image reconstruction at a lower base resolution, thus reducing streaking artifacts and improving the accuracy of image co-registrations. Finally, the methods developed were applied to two fetal scans. The radial sequence was shown to be more motion-robust than an equivalent Cartesian sequence. The minimum number of diametric spokes that provided navigator images that could be accurately co-registered when scanning an adult brain was N=256, which could be acquired in 1.25 s. For abdominal scans, the minimum number of spokes was N=1024, which could be acquired in about 6 s when water excitation is applied. However, the latter could potentially be reduced by reconstructing navigator images at a lower base resolution. Although fetal scans demonstrated poor image contrast, navigator images were able to track motion during the acquisition demonstrating the potential use of this method for self-navigation. In conclusion, a motion-robust radial sequence is presented with potential applications for prospective navigation during fetal MRI.

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Guardiola, Garcia Marta. "Multi-antenna multi-frequency microwave imaging systems for biomedical applications." Doctoral thesis, Universitat Politècnica de Catalunya, 2013. http://hdl.handle.net/10803/134967.

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Medical imaging refers to several different technologies that are used to view the human body in order to diagnose, monitor, or treat medical conditions. Each type of technology gives different information about the area of the body being studied depending on the radiation used to illuminate de body. Nowadays there are still several lesions that cannot be detected with the current methods in a curable stage of the disease. Moreover they present some drawbacks that limit its use, such as health risk, high price, patient discomfort, etc. In the last decades, active microwave imaging systems are being considered for the internal inspection of light-opaque materials thanks to its capacity to penetrate and differentiate their constituents based on the contrast in dielectric properties with a sub-centimeter resolution. Moreover, they are safe, relatively low-cost and portable. Driven by the promising precedents of microwaves in other fields, an active electromagnetic research branch was focused to medical microwave imaging. The potential in breast cancer detection, or even in the more challenging brain stroke detection application, were recently identified. Both applications will be treated in this Thesis. Intensive research in tomographic methods is now devoted to develop quantitative iterative algorithms based on optimizing schemes. These algorithms face a number of problems when dealing with experimental data due to noise, multi-path or modeling inaccuracies. Primarily focused in robustness, the tomographic algorithm developed and assessed in this thesis proposes a non-iterative and non-quantitative implementation based on a modified Born method. Taking as a reference the efficient, real-time and robust 2D circular tomographic method developed in our department in the late 80s, this thesis proposes a novel implementation providing an update to the current state-of-the-art. The two main contributions of this work are the 3D formulation and the multi-frequency extension, leading to the so-called Magnitude Combined (MC) Tomographic algorithm. First of all, 2D algorithms were only applicable to the reconstruction of objects that can be assumed uniform in the third dimension, such as forearms. For the rest of the cases, a 3D algorithm was required. Secondly, multi-frequency information tends to stabilize the reconstruction removing the frequency selective artifacts while maintaining the resolution of the higher frequency of the band. This thesis covers the formulation of the MC tomographic algorithm and its assessment with medically relevant scenarios in the framework of breast cancer and brain stroke detection. In the numerical validation, realistic models from magnetic resonances performed to real patients have been used. These models are currently the most realistic ones available to the scientific community. Special attention is devoted to the experimental validation, which constitutes the main challenge of the microwave imaging systems. For this reason, breast phantoms using mixtures of chemicals to mimic the dielectric properties of real tissues have been manufactured and an acquisition system to measure these phantoms has been created. The results show that the proposed algorithm is able to provide robust images of medically realistic scenarios and detect a malignant breast lesion and a brain hemorrhage, both at an initial stage.

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Martin, Matthieu. "Reconstruction 3D de données échographiques du cerveau du prématuré et segmentation des ventricules cérébraux et thalami par apprentissage supervisé." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEI118.

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Environ 15 millions d’enfants naissent prématurément chaque année dans le monde. Ces patients peuvent présenter des anomalies du développement cérébral qui peuvent causer des troubles du neuro-développement : paralysie cérébrale, surdité, cécité, retard du développement intellectuel, … Des études ont montrées que la quantification du volume des structures cérébrales est un bon indicateur qui permet de réduire ces risques et de les pronostiquer pour orienter les patients dans des parcours de soins adaptés pendant l’enfance. Cette thèse a pour objectif de montrer que l’échographie 3D pourrait être une alternative à l’IRM qui permettrait de quantifier le volume des structures cérébrales chez 100 % des prématurés. Ce travail se focalise plus particulièrement sur la segmentation des ventricules latéraux (VL) et des Thalami, il apporte trois contributions principales : le développement d’un algorithme de création de données échographiques 3D à partir d’échographie transfontanellaire 2D du cerveau du prématuré, la segmentation des ventricules latéraux et des thalami dans un temps clinique et l’apprentissage par des réseaux de neurones convolutionnels (CNN) de la position anatomique des ventricules latéraux. En outre, nous avons créé plusieurs bases de données annotées en partenariat avec le CH d’Avignon. L’algorithme de création de données échographiques 3D a été validé in-vivo où une précision de 0.69 ± 0.14 mm a été obtenue sur le corps calleux. Les VL et les thalami ont été segmentés par apprentissage profond avec l’architecture V-net. Les segmentations ont été réalisées en quelques secondes par ce CNN et des Dice respectifs de 0.828 ± 0.044 et de 0.891 ± 0.016 ont été obtenus. L’apprentissage de la position anatomique des VL a été réalisée via un CPPN (Compositional Pattern Producing Network), elle a permis d’améliorer significativement la précision de V-net lorsqu’il était composé de peu de couches, faisant passer le Dice de 0.524 ± 0.076 à 0.724 ± 0.107 dans le cas d’un réseau V-net à 7 couches. Cette thèse montre qu’il est possible de segmenter automatiquement, avec précision et dans un temps clinique, des structures cérébrales de l’enfant prématuré dans des données échographiques 3D. Cela montre qu’une échographie 3D de haute qualité pourrait être utilisée en routine clinique pour quantifier le volume des structures cérébrales et ouvre la voie aux études d’évaluation de son bénéfice pour les patients About 15 million children are born prematurely each year worldwide. These patients are likely to suffer from brain abnormalities that can cause neurodevelopmental disorders: cerebral palsy, deafness, blindness, intellectual development delay, … Studies have shown that the volume of brain structures is a good indicator which enables to reduce and predict these risks in order to guide patients through appropriate care pathways during childhood. This thesis aims to show that 3D ultrasound could be an alternative to MRI that would enable to quantify the volume of brain structures in all premature infants. This work focuses more particularly on the segmentation of the lateral ventricles (VL) and thalami. Its four main contributions are: the development of an algorithm which enables to create 3D ultrasound data from 2D transfontanellar ultrasound of the premature brain, the segmentation of thigh quality he lateral ventricles and thalami in clinical time and the learning by a convolutional neural networks (CNN) of the anatomical position of the lateral ventricles. In addition, we have created several annotated databases in partnership with the CH of Avignon. Our reconstruction algorithm was used to reconstruct 25 high-quality ultrasound volumes. It was validated in-vivo where an accuracy 0.69 ± 0.14 mm was obtained on the corpus callosum. The best segmentation results were obtained with the V-net, a 3D CNN, which segmented the CVS and the thalami with respective Dice of 0.828± 0.044 and 0.891±0.016 in a few seconds. Learning the anatomical position of the CVS was achieved by integrating a CPPN (Compositional Pattern Producing Network) into the CNNs. It significantly improved the accuracy of CNNs when they had few layers. For example, in the case of the 7-layer V-net network, the Dice has increased from 0.524± 0.076 to 0.724±0.107. This thesis shows that it is possible to automatically segment brain structures of the premature infant into 3D ultrasound data with precision and in a clinical time. This proves that high quality 3D ultrasound could be used in clinical routine to quantify the volume of brain structures and paves the way for studies to evaluate its benefit to patients

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Tounekti, Slimane. "Développements des méthodes d'acquisition à haute résolution spatiale en IRM de diffusion." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSE1008/document.

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L’IRM de diffusion (IRMd) est l’unique technique non invasive qui permet l’exploration de la microstructure cérébrale. En plus d’une large utilisation pour les applications médicales, l’IRMd est aussi utilisée en neuroscience pour comprendre l’organisation et le fonctionnement du cerveau. Toutefois, sa faible résolution spatiale et sa sensibilité aux artéfacts limitent son utilisation chez le primate non humain.L’objectif de cette étude est de développer une nouvelle approche qui permette d’acquérir des données d’IRMd à très haute résolution spatiale sur des cerveaux de macaques anesthésiés. Cette méthode est basée sur un balayage 3D de l’espace de Fourier avec un module de lecture d’Echo Planar-segmenté.Cette méthode a été tout d’abord implémentée sur une machine IRM 3 Tesla (Prisma, Siemens), puis validée et optimisée in-vitro et in-vivo. Par rapport à la méthode d’acquisition classique, un gain de sensibilité de l’ordre de 3 pour la substance grise cérébrale et de 4.7 pour la substance blanche cérébrale a été obtenu grâce à la méthode développée.Cette méthode a permis de réaliser l’IRMd du cerveau de Macaque avec une résolution spatiale isotrope de 0.5 mm jamais atteinte auparavant. L’intérêt de réaliser des données d’IRMd à une telle résolution pour visualiser et analyser in-vivo des structures fines non détectables avec la méthode d’acquisition classique comme les sous-champs de l’hippocampe ou encore la substance blanche superficielle, a été démontré dans cette étude. Des résultats préliminaires très encourageants ont également été obtenus chez l’homme Diffusion MRI (dMRI) is the unique non-invasive technique that allows exploring the cerebral microstructure. Besides a wide use for medical applications, dMRI is also employed in neuroscience to understand the brain organization and connectivity. However, the low spatial resolution and the sensitivity to artefacts limit its application to non-human primates.This work aims to develop a new approach that allows to acquire dMRI at very high spatial resolution on anesthetized macaque brains. This method is based on a 3D sampling of Fourier space with a segmented Echo Planar imaging readout module. This method has been firstly implemented on a 3 Tesla MR scanner (Prisma, Siemens), validated and optimized in-vitro and in-vivo. Compared to the conventional acquisition method, a gain of sensitivity of 3 for the cerebral grey matter and of 4.7 for the white matter was obtained with the proposed approach.This method allowed us to acquire dMRI data on the macaque brain with a spatial isotropic resolution of 0.5 mm ever reached before. The interest to acquire dMRI data with such a spatial resolution to visualize and analyze in-vivo fine structures not detectable with the classical acquisition method, like the sub-fields of hippocampus and the superficial white matter, has also illustrated in this study. Finally, very encouraging preliminary results were also obtained in humans

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Habermehl, Christina Verfasser], Jens [Akademischer Betreuer] Steinbrink, Christoph [Akademischer Betreuer] Schmitz, Klaus-Robert [Akademischer Betreuer] [Müller, and Hamid [Akademischer Betreuer] Dehghani. "High-resolution 3D diffuse optical tomography for non-invasive functional brain imaging in the sub-centimeter range / Christina Habermehl. Gutachter: Klaus-Robert Müller ; Hamid Dehghani ; Jens Steinbrink. Betreuer: Jens Steinbrink ; Christoph Schmitz." Berlin : Technische Universität Berlin, 2014. http://d-nb.info/1066549095/34.

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Habermehl, Christina [Verfasser], Jens Akademischer Betreuer] Steinbrink, Christoph [Akademischer Betreuer] Schmitz, Klaus-Robert [Akademischer Betreuer] [Müller, and Hamid [Akademischer Betreuer] Dehghani. "High-resolution 3D diffuse optical tomography for non-invasive functional brain imaging in the sub-centimeter range / Christina Habermehl. Gutachter: Klaus-Robert Müller ; Hamid Dehghani ; Jens Steinbrink. Betreuer: Jens Steinbrink ; Christoph Schmitz." Berlin : Technische Universität Berlin, 2014. http://d-nb.info/1066549095/34.

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Murtin, Chloé Isabelle. "Traitement d’images de microscopie confocale 3D haute résolution du cerveau de la mouche Drosophile." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEI081/document.

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La profondeur possible d’imagerie en laser-scanning microscopie est limitée non seulement par la distance de travail des lentilles de objectifs mais également par la dégradation de l’image causée par une atténuation et une diffraction de la lumière passant à travers l’échantillon. Afin d’étendre cette limite, il est possible, soit de retourner le spécimen pour enregistrer les images depuis chaque côté, or couper progressivement la partie supérieure de l’échantillon au fur et à mesure de l‘acquisition. Les différentes images prises de l’une de ces manières doivent ensuite être combinées pour générer un volume unique. Cependant, des mouvements de l’échantillon durant les procédures d’acquisition engendrent un décalage non seulement sur en translation selon les axes x, y et z mais également en rotation autour de ces même axes, rendant la fusion entres ces multiples images difficile. Nous avons développé une nouvelle approche appelée 2D-SIFT-in-3D-Space utilisant les SIFT (scale Invariant Feature Transform) pour atteindre un recalage robuste en trois dimensions de deux images. Notre méthode recale les images en corrigeant séparément les translations et rotations sur les trois axes grâce à l’extraction et l’association de caractéristiques stables de leurs coupes transversales bidimensionnelles. Pour évaluer la qualité du recalage, nous avons également développé un simulateur d’images de laser-scanning microscopie qui génère une paire d’images 3D virtuelle dans laquelle le niveau de bruit et les angles de rotations entre les angles de rotation sont contrôlés avec des paramètres connus. Pour une concaténation précise et naturelle de deux images, nous avons également développé un module permettant une compensation progressive de la luminosité et du contraste en fonction de la distance à la surface de l’échantillon. Ces outils ont été utilisés avec succès pour l’obtention d’images tridimensionnelles de haute résolution du cerveau de la mouche Drosophila melanogaster, particulièrement des neurones dopaminergiques, octopaminergiques et de leurs synapses. Ces neurones monoamines sont particulièrement important pour le fonctionnement du cerveau et une étude de leur réseau et connectivité est nécessaire pour comprendre leurs interactions. Si une évolution de leur connectivité au cours du temps n’a pas pu être démontrée via l’analyse de la répartition des sites synaptiques, l’étude suggère cependant que l’inactivation de l’un de ces types de neurones entraine des changements drastiques dans le réseau neuronal Although laser scanning microscopy is a powerful tool for obtaining thin optical sections, the possible depth of imaging is limited by the working distance of the microscope objective but also by the image degradation caused by the attenuation of both excitation laser beam and the light emitted from the fluorescence-labeled objects. Several workaround techniques have been employed to overcome this problem, such as recording the images from both sides of the sample, or by progressively cutting off the sample surface. The different views must then be combined in a unique volume. However, a straightforward concatenation is often not possible, because the small rotations that occur during the acquisition procedure, not only in translation along x, y and z axes but also in rotation around those axis, making the fusion uneasy. To address this problem we implemented a new algorithm called 2D-SIFT-in-3D-Space using SIFT (scale Invariant Feature Transform) to achieve a robust registration of big image stacks. Our method register the images fixing separately rotations and translations around the three axes using the extraction and matching of stable features in 2D cross-sections. In order to evaluate the registration quality, we created a simulator that generates artificial images that mimic laser scanning image stacks to make a mock pair of image stacks one of which is made from the same stack with the other but is rotated arbitrarily with known angles and filtered with a known noise. For a precise and natural-looking concatenation of the two images, we also developed a module progressively correcting the sample brightness and contrast depending on the sample surface. Those tools we successfully used to generate tridimensional high resolution images of the fly Drosophila melanogaster brain, in particular, its octopaminergic and dopaminergic neurons and their synapses. Those monoamine neurons appear to be determinant in the correct operating of the central nervous system and a precise and systematic analysis of their evolution and interaction is necessary to understand its mechanisms. If an evolution over time could not be highlighted through the pre-synaptic sites analysis, our study suggests however that the inactivation of one of these neuron types triggers drastic changes in the neural network

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Nazaran, Amin. "Ultra Short MR Relaxometry and Histological Image Processing for Validation of Diffusion MRI." BYU ScholarsArchive, 2016. https://scholarsarchive.byu.edu/etd/6348.

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Magnetic Resonance Imaging (MRI) is an imaging modality that acquires an image with little to no damage to the tissue. MRI does not introduce foreign particles or high energy radiation into the body, making it one of the least invasive medical imaging modalities. MRI can achieve excellent soft tissue contrast and is therefore useful for diagnosis of a wide variety of diseases. While there are a wide variety of available techniques for generating contrast in MRI, there are still many open areas for research. For example, many tissues in the human body exhibit such rapid signal decay that they are difficult to image with MRI: they are "MRI invisible". Furthermore, some of the newer MRI imaging techniques have not been fully validated to ensure that they are truly revealing accurate information about the underlying anatomical microstructure that they purport to image. This dissertation focuses on the development of new techniques in two distinct areas. First, a novel method for accurately assessing the MRI signal decay properties of tissues that are normally MRI invisible, such as tendons, ligaments, and certain pathological chemical deposits in the brain, is presented. This is termed "ultrashort MRI relaxometry". Second, two new image processing algorithms that operate on high resolution images of stained histological slices of the ex vivo brain are presented. The first of these image processing algorithms allows the semi-automated extraction of nerve fiber directionality from the histological slice images, a process that is normally done manually, is incredibly time consuming, and is prone to human error. This new technique represents one significant step in the complicated problem of attempting to validate a popular MRI technique, Diffusion Tensor Imaging (DTI), by ensuring that DTI results correlate with the true underlying physiology revealed by histological slicing and staining. The second of these image processing algorithms attempts to extract and segment regions of different "cytoarchitectonic characteristics" from stained histological slices of ex vivo brain. Again, traditional cytoarchitectonic segmentation relies on manual segmentation by an expert neuroanatomist, which is slow and sometimes inconsistent. The new technique is a first step towards automated this process, potentially providing greater accuracy and repeatability of the segmentations in a much shorter time. Together, these contributions represent a significant contribution to the body of MR imaging techniques, and associated image processing techniques for validation of newer MR neuroimaging techniques against the gold standard of stained histological slices of ex vivo brain.

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ARAÚJO, Caio Fernandes. "Segmentação de imagens 3D utilizando combinação de imagens 2D." Universidade Federal de Pernambuco, 2016. https://repositorio.ufpe.br/handle/123456789/21040.

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Submitted by Rafael Santana (rafael.silvasantana@ufpe.br) on 2017-08-30T18:18:41Z No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Dissertacao Caio Fernandes Araujo Versão Biblioteca.pdf: 4719896 bytes, checksum: 223db1c4382e6f970dc2cd659978ab60 (MD5) Made available in DSpace on 2017-08-30T18:18:42Z (GMT). No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Dissertacao Caio Fernandes Araujo Versão Biblioteca.pdf: 4719896 bytes, checksum: 223db1c4382e6f970dc2cd659978ab60 (MD5) Previous issue date: 2016-08-12 CAPES Segmentar imagens de maneira automática é um grande desafio. Apesar do ser humano conseguir fazer essa distinção, em muitos casos, para um computador essa divisão pode não ser tão trivial. Vários aspectos têm de ser levados em consideração, que podem incluir cor, posição, vizinhanças, textura, entre outros. Esse desafio aumenta quando se passa a utilizar imagens médicas, como as ressonâncias magnéticas, pois essas, além de possuírem diferentes formatos dos órgãos em diferentes pessoas, possuem áreas em que a variação da intensidade dos pixels se mostra bastante sutil entre os vizinhos, o que dificulta a segmentação automática. Além disso, a variação citada não permite que haja um formato pré-definido em vários casos, pois as diferenças internas nos corpos dos pacientes, especialmente os que possuem alguma patologia, podem ser grandes demais para que se haja uma generalização. Mas justamente por esse possuírem esses problemas, são os principais focos dos profissionais que analisam as imagens médicas. Este trabalho visa, portanto, contribuir para a melhoria da segmentação dessas imagens médicas. Para isso, utiliza a ideia do Bagging de gerar diferentes imagens 2D para segmentar a partir de uma única imagem 3D, e conceitos de combinação de classificadores para uni-las, para assim conseguir resultados estatisticamente melhores, se comparados aos métodos populares de segmentação. Para se verificar a eficácia do método proposto, a segmentação das imagens foi feita utilizando quatro técnicas de segmentação diferentes, e seus resultados combinados. As técnicas escolhidas foram: binarização pelo método de Otsu, o K-Means, rede neural SOM e o modelo estatístico GMM. As imagens utilizadas nos experimentos foram imagens reais, de ressonâncias magnéticas do cérebro, e o intuito do trabalho foi segmentar a matéria cinza do cérebro. As imagens foram todas em 3D, e as segmentações foram feitas em fatias 2D da imagem original, que antes passa por uma fase de pré-processamento, onde há a extração do cérebro do crânio. Os resultados obtidos mostram que o método proposto se mostrou bem sucedido, uma vez que, em todas as técnicas utilizadas, houve uma melhoria na taxa de acerto da segmentação, comprovada através do teste estatístico T-Teste. Assim, o trabalho mostra que utilizar os princípios de combinação de classificadores em segmentações de imagens médicas pode apresentar resultados melhores. Automatic image segmentation is still a great challenge today. Despite the human being able to make this distinction, in most of the cases easily and quickly, to a computer this task may not be that trivial. Several characteristics have to be taken into account by the computer, which may include color, position, neighborhoods, texture, among others. This challenge increases greatly when it comes to using medical images, like the MRI, as these besides producing images of organs with different formats in different people, have regions where the intensity variation of pixels is subtle between neighboring pixels, which complicates even more the automatic segmentation. Furthermore, the above mentioned variation does not allow a pre-defined format in various cases, because the internal differences between patients bodies, especially those with a pathology, may be too large to make a generalization. But specially for having this kind of problem, those people are the main targets of the professionals that analyze medical images. This work, therefore, tries to contribute to the segmentation of medical images. For this, it uses the idea of Bagging to generate different 2D images from a single 3D image, and combination of classifiers to unite them, to achieve statistically significant better results, if compared to popular segmentation methods. To verify the effectiveness of the proposed method, the segmentation of the images is performed using four different segmentation techniques, and their combined results. The chosen techniques are the binarization by the Otsu method, K-Means, the neural network SOM and the statistical model GMM. The images used in the experiments were real MRI of the brain, and the dissertation objective is to segment the gray matter (GM) of the brain. The images are all in 3D, and the segmentations are made using 2D slices of the original image that pass through a preprocessing stage before, where the brain is extracted from the skull. The results show that the proposed method is successful, since, in all the applied techniques, there is an improvement in the accuracy rate, proved by the statistical test T-Test. Thus, the work shows that using the principles of combination of classifiers in medical image segmentation can obtain better results.

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31

Kadalie, Emile. "Development of multi-parametric human MRI at 3T." Electronic Thesis or Diss., Bordeaux, 2023. http://www.theses.fr/2023BORD0493.

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L'Imagerie par Résonance Magnétique (IRM) est une méthode de choix pour le diagnostic, le pronostic et le suivi de pathologies des tissus mous. En effet, les forts contrastes entre les tissus peuvent être modulés à la demande. Cette technique n’a jusqu’à présent montré aucune influence néfaste, permettant des examens répétitifs à haute résolution.L’IRM quantitative (IRMq) est extrêmement intéressante, car elle fournit des cartes dans lesquelles chaque pixel contient une mesure d’un paramètre physique. Contrairement aux images conventionnelles, cette quantification aide à l’interprétation objective des images et fournit une échelle de comparaison entre examens et entre les patients.Parmi les paramètres physiques quantifiables, les temps de relaxation longitudinale (T1) et transversale (T2) sont les plus courants.La séquence Dual Echo Steady State (DESS) est utilisée en IRM ostéoarticulaire pour obtenir rapidement des images anatomiques et une cartographie T2 3D. En acquérant deux échos distincts, deux images à contrastes différents sont reconstruites. Leur rapport est utilisé pour obtenir des cartes T2, en le faisant correspondre à un dictionnaire calculé à partir de nombreux signaux simulés. Néanmoins, la séquence est sensible au mouvement, générant des artefacts et des variations dans les mesures de T2. Par conséquent, l’objectif principal de mon travail a été de développer une séquence DESS 3D rapide pour l’imagerie cérébrale permettant une estimation précise de T2 et une répétabilité élevée à 3T.Pour cela, j'ai d'abord identifié la cause de l'artefact présent sur les images cérébrales, grâce à l'insertion d'un module d’auto-synchronisation (SG). Sa phase étant corrélée au signal d'une ceinture respiratoire, les variations de B0 dues à la respiration ont ainsi été identifiées comme la source des artefact.Pour corriger cet artefact, une trajectoire spécifique à la technique Compressed Sensing (CS) a été optimisée pour regrouper rétrospectivement les données en plusieurs phases respiratoires et reconstruire les espaces de Fourier sous-échantillonnés en images de haute qualité. Pour augmenter la répétabilité de la méthode, l’encodage cartésien conventionnel a été remplacé par un encodage cartésien spiralé, qui répartit l'artefact sous forme de bruit sur les images. Des cartes 3D T2 ont ensuite été acquises avec une résolution spatiale isotrope de 1,2 mm, et étaient de haute qualité et reproductibles sur tous les volontaires.J’ai prouvé que la méthode d’acquisition couplée à la méthode de reconstruction mises en place au cours de cette thèse pouvait être utilisée sur des images obtenues à partir de différents imageurs, et de différents champs magnétiques (1,5T et 7T).Malgré ces améliorations, les valeurs de T2 sont courtes par rapport à une séquence Spin-Echo. Des simulations ont mis en évidence l’influence des variations de B0 sur les erreurs de T2, ainsi que la forte sensibilité de la DESS aux composantes à T2 courts. Pour corriger les mesures, un dictionnaire incluant des variations de B0 a été créé dans le cas où la séquence DESS serait appliquée sur un organe en mouvement comme le foie.Comme le T1 et le B1 doivent être mesurés pour corriger les mesures de T2, une estimation simultanée du T1 et T2 a été étudiée. Les trains d'écho de gradient au sein de la séquence MP2RAGE ont ainsi été remplacés par des trains DESS. L'optimisation des paramètres de séquence a été explorée via la méthode Cramer Rao Lower Bound afin d'obtenir des cartes T1 et T2 précises.En conclusion, grâce à l’implémentation d'un module d'auto-synchronisation, d'un encodage cartésien spiralé et d'une reconstruction Compressed-Sensing, la nouvelle séquence DESS permet une estimation rapide et répétable du T2 dans l'ensemble du cerveau, en 3D, à plusieurs champs magnétiques.Des améliorations sont nécessaires pour améliorer la précision du T2 et quantifier simultanément plusieurs paramètres via l'application d'une seule séquence Magnetic Resonance Imaging (MRI) is a method of choice for the diagnosis, prognosis and monitoring of pathologies in soft tissues. Indeed, strong contrasts between tissues are obtained and can be modulated on demand. This imaging technique has not shown any harmful influence, enabling repetitive high-resolution exams.Quantitative MRI (qMRI) has become incredibly interesting these last ten years, as it provides maps in which each pixel contains a measurement of a physical parameter. As such, contrarily to conventional images obtained on a gray scale, this MR quantification can be employed to obtain objective interpretations of the images, and to provide a scale for comparing time points and patients.Among the physics parameters that can be quantified, the longitudinal (T1) and the transversal (T2) relaxation times are the most common.The Dual Echo Steady State (DESS) sequence has often been used in musculo-skeletal MRI to rapidly obtain high-contrast morphological images and 3D quantitative T2 mapping. By acquiring two distinct steady-state free precession echoes, two images with different contrasts are built, whose ratio can be used to procure T2 maps by matching it to a computed dictionary of many simulated signals. Nonetheless, the sequence has often been described as sensitive to physiological motion, generating artifacts as well as discrepancies in T2 values. Consequently, the main objective of my work was to implement a rapid 3D DESS sequence for brain imaging that enables T2 estimation accurately and with high repeatability at 3T.To do so, I first identified the cause of the ghosting artifact present in the DESS brain images, through the insertion of a Self-Gating (SG) module. As, its phase was correlated to the signal retrieved from a respiratory belt, B0 variations due to breathing were consequently identified as the source of the ghosting on the brain images.To correct this artifact, a Compressed Sensing dedicated trajectory was implemented so as to retrospectively bin the data into multiple respiratory phases, and reconstruct undersampled k-spaces into images with high quality. To increase the repeatability of the method, the conventional Cartesian encoding was replaced by a Spiral Cartesian encoding, which further distributed the artifact as noise on the images. 3D T2 maps were then acquired with a spatial resolution of 1.2mm isotropic, and were of high quality and repeatable on all the volunteers.The new methodology was then implemented on a 1.5T and a 7T Siemens scanners. This proved that the corrected DESS method set in place during this PhD can be used on images obtained from different scanners, and different magnetic fields.Despite these improvements, the brain T2 values remained short compared to a Spin-Echo sequence. To investigate this issue, several simulations were performed and highlighted the influence of B0 variations in the T2 errors, as well as the high sensitivity to short T2 components. To correct the measurements, a dictionary taking into account multiple B0 variations was created. This will be useful in the case where the DESS sequence is applied on a moving organ like the liver.Also, as additional sequences have to be inserted into the protocol to correct the T2 measurements, a simultaneous T1 and T2 estimation was investigated. To reach this goal, the gradient echo trains within the MP2RAGE sequence were replaced by DESS trains. Sequence parameter optimization was explored via the Cramer Rao Lower Bound method so as to obtain both accurate T1 and T2 maps.In conclusion, through the implementation of a self-gating module, a spiral Cartesian encoding and a Compressed-Sensing acceleration, the new DESS sequence allows a rapid and repeatable estimation of T2 in the whole brain in 3D at multiple magnetic fields.Further improvements are needed to improve the T2 accuracy, and to simultaneously measure multiple quantitative parameters though the application of one sequence

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Pinto, Sílvia Cristina Dias. "Análise de formas 3D usando wavelets 1D, 2D e 3D." Universidade de São Paulo, 2005. http://www.teses.usp.br/teses/disponiveis/76/76132/tde-02052007-085441/.

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Este trabalho apresenta novos métodos para análise de formas tridimensionais dentro do contexto de visão computacional, destacando-se o uso das transformadas wavelets 1D, 2D e 3D, as quais proporcionam uma análise multi-escala das formas estudadas. As formas analisadas se dividem em três tipos diferentes, dependendo da sua representação matemática: f(t)=(x(t),y(t),z(t)), f(x,y)=z e f(x,y,z)=w. Cada tipo de forma é analisado por um método melhor adaptado. Primeiramente, tais formas passam por uma rotina de pré-processamento e, em seguida, pela caracterização por meio da aplicação das transformadas wavelet 1D, 2D e 3D para as respectivas formas. Esta aplicação nos permite extrair características que sejam invariantes à rotação e translação, levando em consideração alguns conceitos matemáticos da geometria diferencial. Destaca-se também neste trabalho a não obrigatoriedade de parametrização das formas. Os resultados obtidos a partir de formas extraídas de imagens médicas e dados biológicos, que justificam este trabalho, são apresentados. This work presents new methods for three-dimensional shape analysis in the context of computational vision, being emphasized the use of 1D, 2D and 3D wavelet transforms, which provide a multiscale analysis of the studied shapes. The analyzed shapes are divided in three different types depending on their representation: f(t)=(x(t),y(t),z(t)), f(x,y)=z and f(x,y,z)=w. Each type of shape is analyzed by a more suitable method. Firstly, such shapes undergo a pre-processing procedure followed by the characterization using the 1D, 2D or 3D wavelet transform, depending on its representation. This application allows to extract features that are rotation- and translation-invariant, based on some mathematical concepts of differential geometry. In this work, we emphasize that it is not necessary to use the parameterized version of the 2D and 3D shapes. The experimental results obtained from shapes extracted from medical and biological images, that corroborate the introduced methods, are presented.

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Bartikian, Mickael Varoujan. "3D atlas of the human brain : ex vivo magnetic resonance imaging." Master's thesis, 2020. http://hdl.handle.net/10451/48284.

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Trabalho Final do Curso de Mestrado Integrado em Medicina, Faculdade de Medicina, Universidade de Lisboa, 2020 Introdução: Os atlas 3D do cérebro são ferramentas essenciais na investigação em neurociências humanas, no ensino da neuroanatomia e no planeamento cirúrgico. Fornecem níveis macroscópicos/microscópicos de informação numa estrutura espacial e permitem a visualização de volumes reconstruídos a partir de dados de Ressonância Magnética (RM), bem como de estudos histológicos. A fusão das duas modalidades combina a precisão dimensional da RM com o detalhe das secções histológicas. Com a evolução da tecnologia de processamento de imagem, é relevante renovar os dados e focar em estruturas anteriormente menos exploradas em atlas, como o hipotálamo, o núcleo basal de Meynert e o núcleo accumbens. Embora existam muitos estudos cerebrais multimodais, vários aspectos podem ser optimizados na preparação do cérebro de cadáver para a RM. Objectivos: Este trabalho constitui a primeira parte da elaboração de um atlas 3D do cérebro humano combinando RM e histologia. O objectivo foi construir um recipiente personalizado para segurar e posicionar um cérebro humano de cadáver adulto na RM, minimizando artefactos de movimento e realizar aquisições volumétricas. Métodos: Um recipiente personalizado foi desenhado e fabricado por impressão 3D para colocar um cérebro de cadáver na RM. Aquisições volumétricas foram obtidas com as sequências T1-MPGR, FGATIR e T2-FLAIR e comparadas quanto ao detalhe anatómico por contraste de substância branca e cinzenta. Resultados: O recipiente do cérebro foi implementado com sucesso, reduzindo a complexidade do protocolo de preparação, e o cérebro foi estabilizado correctamente durante a ressonância magnética. Discussão: Com melhorias, o uso de um recipiente personalizado fabricado por impressão 3D pode ajudar na optimização e padronização da preparação de cérebros de cadáver para RM. As sequências T1-MPGR e FGATIR forneceram a melhor qualidade para detalhes anatómicos Conclusão: A criação do recipiente abordou vários problemas da preparação para RM de cérebro de cadáver. As imagens foram obtidas com sucesso e serão usadas nas etapas seguintes do projecto. Introduction: 3D brain atlases are essential tools in human brain research, neuroanatomy teaching, and surgical planning. They can provide macroscopic/microscopic levels of information in a spatial framework and allow visualisation of reconstructed volumes from MRI data of in/ex vivo brains as well as histological studies. Fusion of both modalities combines the dimensional accuracy of MRI with the detail of histological sections. As image processing technology evolves, it is relevant to renew the data and focus on previously less explored structures, such as the hypothalamus, the nucleus basalis of Meynert and the nucleus accumbens. Although many multimodal brain studies exist, several aspects of the post-mortem preparation for MRI can be optimised. Objectives: This work is the first part of the construction of a 3D atlas of the human brain combining ex vivo MRI and histology. The goal was to build an MRI compatible custom-made container to securely hold an ex vivo adult human brain, minimising movement artifacts, and to perform an MRI scan of the brain. Methods: A custom-shaped container was designed and 3D printed to hold an ex vivo human brain in position in the MRI scanner. Volumetric acquisitions were obtained with T1-MPGR, FGATIR, and T2-FLAIR pulse sequences and compared for their anatomical detail by grey matter to white matter contrast. Results: The brain container was successfully implemented, reducing the complexity of the preparation protocol, and the brain was correctly positioned and stabilised during MRI scanning. Discussion: With some improvements, the use of a 3D-printed custom container can be a step towards the optimisation and standardisation of ex vivo brain preparation for MRI. The T1-MPGR and FGATIR sequences provided the best image quality for anatomical detail Conclusion: Designing the container addressed several issues with ex vivo brain preparation for MRI. Imaging data were successfully obtained and will be used in the following steps of the 3D brain atlas project.

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Lindsey, Brooks. "The Ultrasound Brain Helmet: Simultaneous Multi-transducer 3D Transcranial Ultrasound Imaging." Diss., 2012. http://hdl.handle.net/10161/6129.

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In this work, I examine the problem of rapid imaging of stroke and present ultrasound-based approaches for addressing it. Specifically, this dissertation discusses aberration and attenuation due to the skull as sources of image degradation and presents a prototype system for simultaneous 3D bilateral imaging via both temporal acoustic windows. This system uses custom sparse array transducers built on flexible multilayer circuits that can be positioned for simultaneous imaging via both temporal acoustic windows, allowing for registration and fusion of multiple real-time 3D scans of cerebral vasculature. I examine hardware considerations for new matrix arrays--transducer design and interconnects--in this application. Specifically, it is proposed that signal-to-noise ratio (SNR) may be increased by reducing the length of probe cables. This claim is evaluated as part of the presented system through simulation, experimental data, and in vivo imaging. Ultimately, gains in SNR of 7 dB are realized by replacing a standard probe cable with a much shorter flex interconnect; higher gains may be possible using ribbon-based probe cables. In vivo images are presented depicting cerebral arteries with and without the use of microbubble contrast agent that have been registered and fused using a search algorithm which maximizes normalized cross-correlation. The scanning geometry of a brain helmet-type system is also utilized to allow each matrix array to serve as a correction source for the opposing array. Aberration is estimated using cross-correlation of RF channel signals followed by least mean squares solution of the resulting overdetermined system. Delay maps are updated and real-time 3D scanning resumes. A first attempt is made at using multiple arrival time maps to correct multiple unique aberrators within a single transcranial imaging volume, i.e. several isoplanatic patches. This adaptive imaging technique, which uses steered unfocused waves transmitted by the opposing or "beacon" array, updates the transmit and receive delays of 5 isoplanatic patches within a 64°×64° volume. In phantom experiments, color flow voxels above a common threshold have increased by an average of 92% while color flow variance decreased by an average of 10%. This approach has been applied to both temporal acoustic windows of two human subjects, yielding increases in echo brightness in 5 isoplanatic patches with a mean value of 24.3 ± 9.1%, suggesting such a technique may be beneficial in the future for improving image quality in non-invasive 3D color flow imaging of cerebrovascular disease including stroke.Acoustic window failure and the possibility of overcoming it using a low frequency, large aperture array are also examined. In performing transcranial ultrasound examinations, 8-29% of patients in a general population may present with window failure, in which it is not possible to acquire clinically useful sonographic information through the temporal acoustic window. The incidence of window failure is higher in the elderly and in populations of African descent, making window failure an important concern for stroke imaging through the intact skull. To this end, I describe the technical considerations, design, and fabrication of low-frequency (1.2 MHz), large aperture (25.3 mm) sparse matrix array transducers for 3D imaging in the event of window failure. These transducers are integrated into the existing system for real-time 3D bilateral transcranial imaging and color flow imaging capabilities at 1.2 MHz are directly compared with arrays operating at 1.8 MHz in a flow phantom with approximately 47 dB/cm0.8/MHz0.8 attenuators. In vivo contrast-enhanced imaging allowed visualization of the arteries of the Circle of Willis in 5 of 5 subjects and 8 of 10 sides of the head despite probe placement outside of the acoustic window. Results suggest that the decrease from approximately 2 to 1 MHz for 3D transcranial ultrasound may be sufficient to allow acquisition of useful images either in individuals with poor windows or outside of the temporal acoustic window by untrained operators in the field. Dissertation

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Bouchard, Matthew Bryan. "2D and 3D high-speed multispectral optical imaging systems for in-vivo biomedical research." Thesis, 2014. https://doi.org/10.7916/D8D798G5.

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Functional optical imaging encompasses the use of optical imaging techniques to study living biological systems in their native environments. Optical imaging techniques are well-suited for functional imaging because they are minimally-invasive, use non ionizing radiation, and derive contrast from a wide range of biological molecules. Modern transgenic labeling techniques, active and inactive exogenous agents, and intrinsic sources of contrast provide specific and dynamic markers of in-vivo processes at subcellular resolution. A central challenge in building functional optical imaging systems is to acquire data at high enough spatial and temporal resolutions to be able to resolve the in-vivo process(es) under study. This challenge is particularly highlighted within neuroscience where considerable effort in the field has focused on studying the structural and functional relationships within complete neurovascular units in the living brain. Many existing functional optical techniques are limited in meeting this challenge by their imaging geometries, light source(s), and/or hardware implementations. In this thesis we describe the design, construction, and application of novel 2D and 3D optical imaging systems to address this central challenge with a specific focus on functional neuroimaging applications. The 2D system is an ultra-fast, multispectral, wide-field imaging system capable of imaging 7.5 times faster than existing technologies. Its camera-first design allows for the fastest possible image acquisition rates because it is not limited by synchronization challenges that have hindered previous multispectral systems. We present the development of this system from a bench top instrument to a portable, low-cost, modular, open source, laptop based instrument. The constructed systems can acquire multispectral images at >75 frames per second with image resolutions up to 512 x 512 pixels. This increased speed means that spectral analysis more accurately reflects the instantaneous state of tissues and allows for significantly improved tracking of moving objects. We describe 3 quantitative applications of these systems to in-vivo research and clinical studies of cortical imaging and calcium signaling in stem cells. The design and source code of the portable system was released to the greater scientific community to help make high-speed, multispectral imaging more accessible to a larger number of dynamic imaging applications, and to foster further development of the software package. The second system we developed is an entirely new, high-speed, 3D fluorescence microscopy platform called Laser-Scanning Intersecting Plane Tomography (L-SIPT). L-SIPT uses a novel combination of light-sheet illumination and off-axis detection to provide en-face 3D imaging of samples. L-SIPT allows samples to move freely in their native environments, enabling a range of experiments not possible with previous 3D optical imaging techniques. The constructed system is capable of acquiring 3D images at rates >20 volumes per second (VPS) with volume resolutions of 1400 x 50 x 150 pixels, over a 200 fold increase over conventional laser scanning microscopes. Spatial resolution is set by choice of telescope design. We developed custom opto-mechanical components, computer raytracing models to guide system design and to characterize the technique's fundamental resolution limits, and phantoms and biological samples to refine the system's performance capabilities. We describe initial applications development of the system to image freely moving, transgenic Drosophila Melanogaster larvae, 3D calcium signaling and hemodynamics in transgenic and exogenously labeled rodent cortex in-vivo, and 3D calcium signaling in acute transgenic rodent cortical brain slices in-vitro.

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Eissa, Amir. "Investigation of gradient echo MRI for blood vessel imaging and susceptibility-weighted imaging in the human brain." Phd thesis, 2010. http://hdl.handle.net/10048/1131.

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Thesis (Ph. D.)--University of Alberta, 2010. Title from pdf file main screen (viewed on July 17, 2010). A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Doctor of Philosophy, [Department of] Physics, University of Alberta. Includes bibliographical references.

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Chen, An-chia, and 陳安嘉. "Image Fusion and 3D Visualization for Head and Neck Magnetic Resonance Angiography and Brain Magnetic Resonance Imaging." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/86501586160936575238.

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碩士 雲林科技大學 工業工程與管理研究所碩士班 96 In Taiwan, there are about 13,000 people per year die from cerebrovascular diseases, the second highest cause of death. Magnetic Resonance Angiography (MRA) is one of the main tools for diagnosis of cerebrovascular diseases, which can provide a complete view of bilateral internal carotid artery and intracranial vessel. Because of the sampling constraints, MRA axial plane only presents a smaller scope of intracranial vessel imaging. Head and neck integrity of the vascular diagnostic information often need comparison with the axial and coronal plane MRA. Brain tumor invasion of the central nervous disease is the most common one, whether benign or malignant tumor, may threaten the patient''s life. Most of brain tumors were growing slowly, patients are difficult to detect early, and when symptoms appear the brain tumors are usually become large. Sometimes, brain tumors will surround the nerves or vessels that resulted in treatment more difficult. In the clinically, Magnetic Resonance Imaging (MRI) is the main tools for diagnosis the brain tumors of the region. In this thesis, we expect to align the axial and coronal plane MRA in order to obtain the complete head and neck vascular information. And brain tumors with blood vessels or nerve actual relative position in the treatment of very important. Therefore, through brain tumors and head and neck vascular imaging integration, can be clearly observed that the brain tumor will move the vessel, or including the vessel. The performance of hybrid Particle Swarm Optimization (hPSO), particle swarm optimization (PSO) and genetic algorithm (GA) for optimal alignment parameters is compared, to enhance clinical research and physician preoperative planning. In this paper, the alignment quality performance of measurement is used root mean square error (RMSE) to measure the algorithms'' quality. The results of performance comparison showed that hPSO outperformed PSO and GA in alignment quality. This paper used pulse coupled neural network (PCNN) algorithms to segment the axial plane vascular image, and used active contours using level sets (ACLS) algorithms to segment the brain tumor image. Finally, the optimal geometric transformation parameters used in brain tumors and head and neck vascular imaging integration. Meanwhile, the fused information is presented as the form of 3D visualization, which provides the integrated information for clinical diagnosis and medical research.

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Lindvere, Liis. "Functional Stimulation Induced Change in Cerebral Blood Volume: A Two Photon Fluorescence Microscopy Map of the 3D Microvascular Network Response." Thesis, 2011. http://hdl.handle.net/1807/31314.

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The current work investigated the stimulation induced spatial response of the cerebral microvascular network by reconstruction of the 3D microvascular morphology from in vivo two photon fluorescence microscopy (2PFM) volumes using an automated, model based tracking algorithm. In vivo 2PFM imaging of the vasculature in the forelimb representation of the primary somatosensory cortex of alpha-chloralose anesthetized rats was achieved via implantation of a closed cranial window, and intravascular injection of fluorescent dextran. The dilatory and constrictory responses of the cerebral microvascular network to functional stimulation were heterogeneous and depended on resting vascular radius and response latency. Capillaries experienced large relative dilations and constrictions, but the larger vessel absolute volume changes dominated the overall network cerebral blood volume change.

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Dissertations / Theses on the topic '3D brain imaging'

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