Dissertations / Theses on the topic '2D Images - 3D Models'
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Zhang, Yan. "Feature-based automatic registration of images with 2D and 3D models." Thesis, University of Central Lancashire, 2006. http://clok.uclan.ac.uk/21603/.
Full textStebbing, Richard. "Model-based segmentation methods for analysis of 2D and 3D ultrasound images and sequences." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:f0e855ca-5ed9-4e40-994c-9b470d5594bf.
Full textLópez, Picazo Mirella. "3D subject-specific shape and density modeling of the lumbar spine from 2D DXA images for osteoporosis assessment." Doctoral thesis, Universitat Pompeu Fabra, 2019. http://hdl.handle.net/10803/666513.
Full textLa osteoporosis es la enfermedad ósea más común, con una morbilidad y mortalidad significativas causadas por el aumento de la fragilidad ósea y la susceptibilidad a las fracturas. La absorciometría de rayos X de energía dual (DXA, por sus siglas en inglés) es la técnica de referencia para la evaluación de la osteoporosis y del riesgo de fracturas en la columna vertebral. Sin embargo, el análisis estándar de las imágenes DXA solo proporciona mediciones 2D y no diferencia entre los compartimentos óseos; tampoco evalúa la densidad ósea en el cuerpo vertebral, que es donde se producen la mayoría de las fracturas osteoporóticas. La tomografía computarizada cuantitativa (QCT, por sus siglas en inglés) es una técnica alternativa que supera las limitaciones del diagnóstico basado en DXA. Sin embargo, debido al alto costo y la dosis de radiación, la QCT no se usa para el diagnóstico de la osteoporosis. En esta tesis, se propone un método que proporciona una estimación personalizada de la forma 3D y la densidad de la columna vertebral en la zona lumbar a partir de una única imagen DXA anteroposterior. El método se basa en un modelo estadístico 3D de forma y densidad creado a partir de un conjunto de entrenamiento de exploraciones QCT. La estimación 3D personalizada de forma y densidad se obtiene al registrar y ajustar el modelo estadístico con la imagen DXA. Se segmentan los compartimentos óseos corticales y trabeculares utilizando un algoritmo basado en modelos. Se realizan mediciones 3D en diferentes regiones vertebrales y compartimentos óseos. La precisión de los métodos propuestos se evalúa comparando las mediciones 3D derivadas de DXA con las derivadas de QCT. También se realizan dos estudios de casos y controles: un estudio retrospectivo que evalúa la capacidad de las mediciones 3D derivadas de DXA en la columna lumbar para discriminar entre sujetos con fracturas vertebrales relacionadas con la osteoporosis y sujetos control; y un estudio que evalúa la asociación entre las mediciones 3D derivadas de DXA en la columna lumbar y las fracturas de cadera relacionadas con la osteoporosis. En ambos estudios, se encuentran asociaciones más fuertes entre las fracturas relacionadas con la osteoporosis y las mediciones 3D derivadas de DXA en comparación con las mediciones estándar 2D. La tecnología desarrollada dentro de esta tesis ofrece un análisis en 3D de la columna lumbar, que podría mejorar la evaluación de la osteoporosis y el riesgo de fractura en pacientes que se sometieron a una exploración DXA estándar de la columna lumbar sin ningún examen adicional.
Wasswa, William. "3D approximation of scapula bone shape from 2D X-ray images using landmark-constrained statistical shape model fitting." Master's thesis, University of Cape Town, 2016. http://hdl.handle.net/11427/23777.
Full textKarlsson, Edlund Patrick. "Methods and models for 2D and 3D image analysis in microscopy, in particular for the study of muscle cells." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-9201.
Full textHua, Xiaoben, and Yuxia Yang. "A Fusion Model For Enhancement of Range Images." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2203.
Full textRoom 401, No.56, Lane 21, Yin Gao Road, Shanghai, China
Ben, Abdallah Hamdi. "Inspection d'assemblages aéronautiques par vision 2D/3D en exploitant la maquette numérique et la pose estimée en temps réel Three-dimensional point cloud analysis for automatic inspection of complex aeronautical mechanical assemblies Automatic inspection of aeronautical mechanical assemblies by matching the 3D CAD model and real 2D images." Thesis, Ecole nationale des Mines d'Albi-Carmaux, 2020. http://www.theses.fr/2020EMAC0001.
Full textThis thesis makes part of a research aimed towards innovative digital tools for the service of what is commonly referred to as Factory of the Future. Our work was conducted in the scope of the joint research laboratory "Inspection 4.0" founded by IMT Mines Albi/ICA and the company DIOTA specialized in the development of numerical tools for Industry 4.0. In the thesis, we were interested in the development of systems exploiting 2D images or (and) 3D point clouds for the automatic inspection of complex aeronautical mechanical assemblies (typically an aircraft engine). The CAD (Computer Aided Design) model of the assembly is at our disposal and our task is to verify that the assembly has been correctly assembled, i.e. that all the elements constituting the assembly are present in the right position and at the right place. The CAD model serves as a reference. We have developed two inspection scenarios that exploit the inspection systems designed and implemented by DIOTA: (1) a scenario based on a tablet equipped with a camera, carried by a human operator for real-time interactive control, (2) a scenario based on a robot equipped with sensors (two cameras and a 3D scanner) for fully automatic control. In both scenarios, a so-called localisation camera provides in real-time the pose between the CAD model and the sensors (which allows to directly link the 3D digital model with the 2D images or the 3D point clouds analysed). We first developed 2D inspection methods, based solely on the analysis of 2D images. Then, for certain types of inspection that could not be performed by using 2D images only (typically requiring the measurement of 3D distances), we developed 3D inspection methods based on the analysis of 3D point clouds. For the 3D inspection of electrical cables, we proposed an original method for segmenting a cable within a point cloud. We have also tackled the problem of automatic selection of best view point, which allows the inspection sensor to be placed in an optimal observation position. The developed methods have been validated on many industrial cases. Some of the inspection algorithms developed during this thesis have been integrated into the DIOTA Inspect© software and are used daily by DIOTA's customers to perform inspections on industrial sites
Truong, Michael Vi Nguyen. "2D-3D registration of cardiac images." Thesis, King's College London (University of London), 2014. https://kclpure.kcl.ac.uk/portal/en/theses/2d3d-registration-of-cardiac-images(afef93e6-228c-4bc7-aab0-94f1e1ecf006).html.
Full textJones, Jonathan-Lee. "2D and 3D segmentation of medical images." Thesis, Swansea University, 2015. https://cronfa.swan.ac.uk/Record/cronfa42504.
Full textLiu, Jianxin. "A porosity-based model for coupled thermal-hydraulic-mechanical processes." University of Western Australia. Centre for Petroleum, Fuels and Energy, 2010. http://theses.library.uwa.edu.au/adt-WU2010.0113.
Full textHuang, Hui. "Efficient reconstruction of 2D images and 3D surfaces." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/2821.
Full textHenrichsen, Arne. "3D reconstruction and camera calibration from 2D images." Master's thesis, University of Cape Town, 2000. http://hdl.handle.net/11427/9725.
Full textA 3D reconstruction technique from stereo images is presented that needs minimal intervention from the user. The reconstruction problem consists of three steps, each of which is equivalent to the estimation of a specific geometry group. The first step is the estimation of the epipolar geometry that exists between the stereo image pair, a process involving feature matching in both images. The second step estimates the affine geometry, a process of finding a special plane in projective space by means of vanishing points. Camera calibration forms part of the third step in obtaining the metric geometry, from which it is possible to obtain a 3D model of the scene. The advantage of this system is that the stereo images do not need to be calibrated in order to obtain a reconstruction. Results for both the camera calibration and reconstruction are presented to verify that it is possible to obtain a 3D model directly from features in the images.
Bowden, Nathan Charles. "Camera based texture mapping: 3D applications for 2D images." Texas A&M University, 2005. http://hdl.handle.net/1969.1/2407.
Full textAllalou, Amin. "Methods for 2D and 3D Quantitative Microscopy of Biological Samples." Doctoral thesis, Uppsala universitet, Centrum för bildanalys, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-159196.
Full textAllouch, Yair. "Multi scale geometric segmentation on 2D and 3D Digital Images /." [Beer Sheva] : Ben Gurion University of the Negev, 2007. http://aranne5.lib.ad.bgu.ac.il/others/AlloucheYair.pdf.
Full textDowell, Rachel J. (Rachel Jean). "Registration of 2D ultrasound images in preparation for 3D reconstruction." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/10181.
Full textCheng, Yuan 1971. "3D reconstruction from 2D images and applications to cell cytoskeleton." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/88870.
Full textIncludes bibliographical references (leaves 121-129).
Approaches to achieve three dimensional (3D) reconstruction from 2D images can be grouped into two categories: computer-vision-based reconstruction and tomographic reconstruction. By exploring both the differences and connections between these two types of reconstruction, the thesis attempts to develop a new technique that can be applied to 3D reconstruction of biological structures. Specific attention is given to the reconstruction of the cell cytoskeleton from electron microscope images. The thesis is composed of two parts. The first part studies computer-vision-based reconstruction methods that extract 3D information from geometric relationship among images. First, a multiple-feature-based stereo reconstruction algorithm that recovers the 3D structure of an object from two images is presented. A volumetric reconstruction method is then developed by extending the algorithm to multiple images. The method integrates a sequence of 3D reconstruction from different stereo pairs. It achieves a globally optimized reconstruction by evaluating certainty values of each stereo reconstruction. This method is tuned and applied to 3D reconstruction of the cell cytoskeleton. Feasibility, reliability and flexibility of the method are explored.
(cont.) The second part of the thesis focuses on a special tomographic reconstruction, discrete tomography, where the object to be reconstructed is composed of a discrete set of materials each with uniform values. A Bayesian labeling process is proposed as a framework for discrete tomography. The process uses an expectation-maximization (EM) algorithm with which the reconstruction is obtained efficiently. Results demonstrate that the proposed algorithm achieves high reconstruction quality even with a small number of projections. An interesting relationship between discrete tomography and conventional tomography is also derived, showing that discrete tomography is a more generalized form of tomography and conventional tomography is only a special case of such generalization.
by Yuan Cheng.
Ph.D.
Mertzanidou, T. "Automatic correspondence between 2D and 3D images of the breast." Thesis, University College London (University of London), 2012. http://discovery.ucl.ac.uk/1362435/.
Full textPhan, Tan Binh. "On the 3D hollow organ cartography using 2D endoscopic images." Electronic Thesis or Diss., Université de Lorraine, 2020. http://www.theses.fr/2020LORR0135.
Full textStructure from motion (SfM) algorithms represent an efficient means to construct extended 3D surfaces using images of a scene acquired from different viewpoints. SfM methods simultaneously determine the camera motion and a 3D point cloud lying on the surfaces to be recovered. Classical SfM algorithms use feature point detection and matching methods to track homologous points across the image sequences, each point track corresponding to a 3D point to be reconstructed. The SfM algorithms exploit the correspondences between homologous points to recover the 3D scene structure and the successive camera poses in an arbitrary world coordinate system. There exist different state-of-the-art SfM algorithms which can efficiently reconstruct different types of scenes, under the condition that the images include enough textures or structures. However, most of the existing solutions are inappropriate, or at least not optimal, when the sequences of images are without or only with few textures. This thesis proposes two dense optical flow (DOF)-based SfM solutions to reconstruct complex scenes using images with few textures and acquired under changing illumination conditions. It is notably shown how accurate DOF fields can be optimally used due to an image selection strategy which both maximizes the number and size of homologous point sets, and minimizes the errors in the homologous point localization. The accuracy of the proposed 3D cartography methods is assessed on phantoms with known dimensions. The robustness and the interest of the proposed methods are demonstrated on various complex medical scenes using a constant algorithm parameter set. The proposed solutions reconstructed organs seen in different medical examinations (epithelial surface of the inner stomach wall, inner epithelial bladder surface, and the skin surface in dermatology) and various imaging modalities (white light for all examinations, green-blue light in gastroscopy and fluorescence in cystoscopy)
Coxon, Thomas Liam. "2D and 3D phenotyping murine models of Amelogenesis imperfecta." Thesis, University of Liverpool, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.539608.
Full textMastin, Dana Andrew. "Statistical methods for 2D-3D registration of optical and LIDAR images." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/55123.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (p. 121-123).
Fusion of 3D laser radar (LIDAR) imagery and aerial optical imagery is an efficient method for constructing 3D virtual reality models. One difficult aspect of creating such models is registering the optical image with the LIDAR point cloud, which is a camera pose estimation problem. We propose a novel application of mutual information registration which exploits statistical dependencies in urban scenes, using variables such as LIDAR elevation, LIDAR probability of detection (pdet), and optical luminance. We employ the well known downhill simplex optimization to infer camera pose parameters. Utilization of OpenGL and graphics hardware in the optimization process yields registration times on the order of seconds. Using an initial registration comparable to GPS/INS accuracy, we demonstrate the utility of our algorithms with a collection of urban images. Our analysis begins with three basic methods for measuring mutual information. We demonstrate the utility of the mutual information measures with a series of probing experiments and registration tests. We improve the basic algorithms with a novel application of foliage detection, where the use of only non-foliage points improves registration reliability significantly. Finally, we show how the use of an existing registered optical image can be used in conjunction with foliage detection to achieve even more reliable registration.
by Dana Andrew Mastin.
S.M.
Qiu, Xuchong. "2D and 3D Geometric Attributes Estimation in Images via deep learning." Thesis, Marne-la-vallée, ENPC, 2021. http://www.theses.fr/2021ENPC0005.
Full textThe visual perception of 2D and 3D geometric attributes (e.g. translation, rotation, spatial size and etc.) is important in robotic applications. It helps robotic system build knowledge about its surrounding environment and can serve as the input for down-stream tasks such as motion planning and physical intersection with objects.The main goal of this thesis is to automatically detect positions and poses of interested objects for robotic manipulation tasks. In particular, we are interested in the low-level task of estimating occlusion relationship to discriminate different objects and the high-level tasks of object visual tracking and object pose estimation.The first focus is to track the object of interest with correct locations and sizes in a given video. We first study systematically the tracking framework based on discriminative correlation filter (DCF) and propose to leverage semantics information in two tracking stages: the visual feature encoding stage and the target localization stage. Our experiments demonstrate that the involvement of semantics improves the performance of both localization and size estimation in our DCF-based tracking framework. We also make an analysis for failure cases.The second focus is using object shape information to improve the performance of object 6D pose estimation and do object pose refinement. We propose to estimate the 2D projections of object 3D surface points with deep models to recover object 6D poses. Our results show that the proposed method benefits from the large number of 3D-to-2D point correspondences and achieves better performance. As a second part, we study the constraints of existing object pose refinement methods and develop a pose refinement method for objects in the wild. Our experiments demonstrate that our models trained on either real data or generated synthetic data can refine pose estimates for objects in the wild, even though these objects are not seen during training.The third focus is studying geometric occlusion in single images to better discriminate objects in the scene. We first formalize geometric occlusion definition and propose a method to automatically generate high-quality occlusion annotations. Then we propose a new occlusion relationship formulation (i.e. abbnom) and the corresponding inference method. Experiments on occlusion reasoning benchmarks demonstrate the superiority of the proposed formulation and method. To recover accurate depth discontinuities, we also propose a depth map refinement method and a single-stage monocular depth estimation method.All the methods that we propose leverage on the versatility and power of deep learning. This should facilitate their integration in the visual perception module of modern robotic systems.Besides the above methodological advances, we also made available software (for occlusion and pose estimation) and datasets (of high-quality occlusion information) as a contribution to the scientific community
ARMANDE, NASSER. "Caracterisation de reseaux fins dans les images 2d et 3d applications : images satellites et medicales." Paris 11, 1997. http://www.theses.fr/1997PA112094.
Full textSdiri, Bilel. "2D/3D Endoscopic image enhancement and analysis for video guided surgery." Thesis, Sorbonne Paris Cité, 2018. http://www.theses.fr/2018USPCD030.
Full textMinimally invasive surgery has made remarkable progress in the last decades and became a very popular diagnosis and treatment tool, especially with the rapid medical and technological advances leading to innovative new tools such as robotic surgical systems and wireless capsule endoscopy. Due to the intrinsic characteristics of the endoscopic environment including dynamic illumination conditions and moist tissues with high reflectance, endoscopic images suffer often from several degradations such as large dark regions,with low contrast and sharpness, and many artifacts such as specular reflections and blur. These challenges together with the introduction of three dimensional(3D) imaging surgical systems have prompted the question of endoscopic images quality, which needs to be enhanced. The latter process aims either to provide the surgeons/doctors with a better visual feedback or improve the outcomes of some subsequent tasks such as features extraction for 3D organ reconstruction and registration. This thesis addresses the problem of endoscopic image quality enhancement by proposing novel enhancement techniques for both two-dimensional (2D) and stereo (i.e. 3D)endoscopic images.In the context of automatic tissue abnormality detection and classification for gastro-intestinal tract disease diagnosis, we proposed a pre-processing enhancement method for 2D endoscopic images and wireless capsule endoscopy improving both local and global contrast. The proposed method expose inner subtle structures and tissues details, which improves the features detection process and the automatic classification rate of neoplastic,non-neoplastic and inflammatory tissues. Inspired by binocular vision attention features of the human visual system, we proposed in another workan adaptive enhancement technique for stereo endoscopic images combining depth and edginess information. The adaptability of the proposed method consists in adjusting the enhancement to both local image activity and depth level within the scene while controlling the interview difference using abinocular perception model. A subjective experiment was conducted to evaluate the performance of the proposed algorithm in terms of visual qualityby both expert and non-expert observers whose scores demonstrated the efficiency of our 3D contrast enhancement technique. In the same scope, we resort in another recent stereo endoscopic image enhancement work to the wavelet domain to target the enhancement towards specific image components using the multiscale representation and the efficient space-frequency localization property. The proposed joint enhancement methods rely on cross-view processing and depth information, for both the wavelet decomposition and the enhancement steps, to exploit the inter-view redundancies together with perceptual human visual system properties related to contrast sensitivity and binocular combination and rivalry. The visual qualityof the processed images and objective assessment metrics demonstrate the efficiency of our joint stereo enhancement in adjusting the image illuminationin both dark and saturated regions and emphasizing local image details such as fine veins and micro vessels, compared to other endoscopic enhancement techniques for 2D and 3D images
Linden, d’Hooghvorst Rodríguez Jean Joseph van der. "Geomechanical study of the Tarfaya basin, West African coast, using 3D/2D static models and 2D evolutionary models." Doctoral thesis, Universitat de Barcelona, 2021. http://hdl.handle.net/10803/672449.
Full textChang, Xianglong. "Semi-automatic fitting of deformable 3D models to 2D sketches." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/797.
Full textRandell, Charles James. "3D underwater monocular machine vision from 2D images in an attenuating medium." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ32764.pdf.
Full textLaw, 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.
Full textZöllei, Lilla 1977. "2D-3D rigid-body registration of X-ray flourscopy and CT images." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/86790.
Full textReddy, Serendra. "Automatic 2D-to-3D conversion of single low depth-of-field images." Doctoral thesis, University of Cape Town, 2017. http://hdl.handle.net/11427/24475.
Full textZhou, Dianle. "Using 3D morphable models for 3D photo-realistic personalized avatars and 2D face recognition." Thesis, Evry, Institut national des télécommunications, 2011. http://www.theses.fr/2011TELE0017/document.
Full textIn the past decade, 3D statistical face model (3D Morphable Model) has received much attention by both the commercial and public sectors. It can be used for face modeling for photo-realistic personalized 3D avatars and for the application 2D face recognition technique in biometrics. This thesis describes how to achieve an automatic 3D face reconstruction system that could be helpful for building photo-realistic personalized 3D avatars and for 2D face recognition with pose variability. The first systems we propose Combined Active Shape Model for 2D frontal facial landmark location and its application in 2D frontal face recognition in degraded condition. The second proposal is 3D Active Shape Model (3D-ASM) algorithm which is presented to automatically locate facial landmarks from different views. The third contribution is to use biometric data (2D images and 3D scan ground truth) for quantitatively evaluating the 3D face reconstruction. Finally, we address the issue of automatic 2D face recognition across pose using 3D Morphable Model
Gomez, Abraham. "2D concept to 3D game model : Production of 3D models for top down games." Thesis, Luleå tekniska universitet, Institutionen för konst, kommunikation och lärande, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-64297.
Full textChaudhary, Priyanka. "SPHEROID DETECTION IN 2D IMAGES USING CIRCULAR HOUGH TRANSFORM." UKnowledge, 2010. http://uknowledge.uky.edu/gradschool_theses/9.
Full textCalafato, Giulia <1993>. "Cytotoxic effect of immunotoxins in 2D and 3D models of sarcoma." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amsdottorato.unibo.it/10050/1/Tesi%20AMS%20Tesi%20di%20Dottorato%20Giulia%20Calafato.pdf.
Full textAgerskov, Niels, and Gabriel Carrizo. "Application for Deriving 2D Images from 3D CT Image Data for Research Purposes." Thesis, KTH, Skolan för teknik och hälsa (STH), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-190881.
Full textPå Karolinska universitetssjukhuset, Huddinge har man länge önskat möjligheten att utföra mallningar av höftproteser med hjälp av data från datortomografiundersökningar (DT). Detta har hittills inte varit möjligt eftersom programmet som används för mallning av höftproteser enbart accepterar traditionella slätröntgenbilder. Därför var syftet med detta projekt att skapa en mjukvaru-applikation som kan användas för att generera 2D-bilder för mallning av proteser från DT-data. För att skapa applikationen användes huvudsakligen Python-kodbiblioteken NumPy och The Visualization Toolkit (VTK) tillsammans med användargränssnittsbiblioteket PyQt4. I applikationen ingår ett grafiskt användargränssnitt och metoder för optimering av bilderna i mallningssammanhang. Applikationen fungerar men bildernas kvalitet måste utvärderas med en större urvalsgrupp.
North, Peter R. J. "The reconstruction of visual appearance by combining stereo surfaces." Thesis, University of Sussex, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362837.
Full textLumpkins, Sarah B. "Space radiation-induced bystander signaling in 2D and 3D skin tissue models." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/70817.
Full textPage 157 blank. Cataloged from PDF version of thesis.
Includes bibliographical references (p. 145-156).
Space radiation poses a significant hazard to astronauts on long-duration missions, and the low fluences of charged particles characteristic of this field suggest that bystander effects, the phenomenon in which a greater number of cells exhibit damage than expected based on the number of cells traversed by radiation, could be significant contributors to overall cell damage. The purpose of this thesis was to investigate bystander effects due to signaling between different cell types cultured within 2D and 3D tissue architectures. 2D bystander signaling was investigated using a transwell insert system in which normal human fibroblasts (A) and keratinocytes (K) were irradiated with 1 GeV/n protons or iron ions at the NASA Space Radiation Laboratory using doses from either 2 Gy (protons) or 1 Gy (iron ions) down to spacerelevant low fluences. Medium-mediated bystander responses were investigated using three cell signaling combinations. Bystander signaling was also investigated in a 3D model by developing tissue constructs consisting of fibroblasts embedded in a collagen matrix with a keratinocyte epidermal layer. Bystander experiments were conducted by splitting each construct in half and exposing half to radiation then placing the other half in direct contact with the irradiated tissue on a transwell insert. Cell damage was evaluated primarily as formation of foci of the DNA repair-related protein 53BP1. In the 2D system, both protons and iron ions yielded a strong dose dependence for the induction of 53BP1 in irradiated cells, while the magnitudes and time courses of bystander responses were dependent on radiation quality. Furthermore, bystander effects were present in all three cell signaling combinations even at the low proton particle fluences used, suggesting the potential importance of including these effects in cancer risk models for low-dose space radiation exposures. Cells cultured in the 3D constructs exhibited a significant reduction in the percentages of both direct and bystander cells positive for 53BP1 foci, although the qualitative kinetics of DNA damage and repair were similar to those observed in 2D. These results provide evidence that the microenvironment significantly influences intercellular signaling and that cells may be more radioresistant in 3D compared to 2D systems.
by Sarah B. Lumpkins.
Sc.D.
Baudour, Alexis. "Détection de filaments dans des images 2D et 3D : modélisation, étude mathématique et algorithmes." Phd thesis, Université de Nice Sophia-Antipolis, 2009. http://tel.archives-ouvertes.fr/tel-00507520.
Full textSintorn, Ida-Maria. "Segmentation methods and shape descriptions in digital images : applications in 2D and 3D microscopy /." Uppsala : Centre for Image Analysis, Swedish University of Agricultural Sciences, 2005. http://epsilon.slu.se/200520.pdf.
Full textBEIL, FRANK MICHAEL. "Approche structurelle de l'analyse de la texture dans les images cellulaires 2d et 3d." Paris 7, 1999. http://www.theses.fr/1999PA077019.
Full textMEZERREG, MOHAMED. "Structures de donnees graphiques : contribution a la conception d'un s.g.b.d. images 2d et 3d." Paris 7, 1990. http://www.theses.fr/1990PA077155.
Full textARAÚJO, 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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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.
Lubniewski, Pawel. "Recalage 3D/2D d'images pour le traitement endovasculaire des dissections aortiques." Thesis, Clermont-Ferrand 1, 2014. http://www.theses.fr/2014CLF1MM24/document.
Full textIn this study, we present our works related to 3D/2D image registrationfor aorti dissition. Its aim is to propose a visualization of medial datawhih an be used by physians during endovas ular proedures.For this purpose, we have proposed a parametrimodel of aorta, alleda Tubular Envelope. It is used to express the global shape and deformationsof the aorta, by a minimal number of parameters. The tubular envelope isused in our image registration algorithms.The registration by ITD (Image Transformation Descriptors) is our ori-ginal method of image alignment : itomputes the rigid 2D transformation between data sets diretly, without any optimization process.We provide thedefinition of this method, as well as the proposition of several descriptors' formulae, in the base of images of aorta. The technique allows us to quickly and a poarse alignment between data. We also propose the extension of theoriginal approach for the registration of 3D and 2D images.The complete chain of 3D/2D image registration techniques, proposedin this document, consists of the ITD stage, followed by an intensity basedhybrid method. The use of our 3D/2D algorithm, based on the image trans-formation descriptors as an initialization phase, reduces the computing timeand improves the efficiency of the presented approach.We have tested our registration methods for the medical images of several patients after endovasular treatment. Results have been approved by our clinical specialists and our approach.We have tested our registration methods for the medical images of several patients after endovascular treatment. Results have been approved by our clinical specialists and our approach may appear in the intervention rooms in the futur
ZAPPINO, ENRICO. "Variable kinematic 1D, 2D and 3D Models for the Analysis of Aerospace Structures." Doctoral thesis, Politecnico di Torino, 2014. http://hdl.handle.net/11583/2573739.
Full textGrandi, Jerônimo Gustavo. "Multidimensional similarity search for 2D-3D medical data correlation and fusion." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2014. http://hdl.handle.net/10183/104133.
Full textImages of the inner anatomy are essential for clinical practice. To establish a correlation between them is an important procedure for diagnosis and treatment. In this thesis, we propose an approach to correlate within-modality 2D and 3D data from ordinary acquisition protocols based solely on the pixel/voxel information. The work was divided into two development phases. First, we explored the similarity problem between medical images using the perspective of image quality assessment. It led to the development of a 2-step technique that settles the compromise between processing speed and precision of two known approaches. We evaluated the quality and applicability of the 2-step and, in the second phase, we extended the method to use similarity analysis to, given an arbitrary slice image (2D), find the location of this slice within the volume data (3D). The solution minimizes the virtually infinite number of possible cross section orientations and uses optimizations to reduce the computational workload and output accurate results. The matching is displayed in a volumetric three-dimensional visualization fusing the 3D with the 2D. An experimental analysis demonstrated that despite the computational complexity of the algorithm, the use of severe data sampling allows achieving a great compromise between performance and accuracy even when performed with low gradient intensity datasets.
Kang, Xin, and 康欣. "Feature-based 2D-3D registration and 3D reconstruction from a limited number of images via statistical inference for image-guidedinterventions." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B48079625.
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Orthopaedics and Traumatology
Doctoral
Doctor of Philosophy
Boui, Marouane. "Détection et suivi de personnes par vision omnidirectionnelle : approche 2D et 3D." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLE009/document.
Full textIn this thesis we will handle the problem of 3D people detection and tracking in omnidirectional images sequences, in order to realize applications allowing3D pose estimation, we investigate the problem of 3D people detection and tracking in omnidirectional images sequences. This requires a stable and accurate monitoring of the person in a real environment. In order to achieve this, we will use a catadioptric camera composed of a spherical mirror and a perspective camera. This type of sensor is commonly used in computer vision and robotics. Its main advantage is its wide field of vision, which allows it to acquire a 360-degree view of the scene with a single sensor and in a single image. However, this kind of sensor generally generates significant distortions in the images, not allowing a direct application of the methods conventionally used in perspective vision. Our thesis contains a description of two monitoring approaches that take into account these distortions. These methods show the progress of our work during these three years, allowing us to move from person detection to the 3Destimation of its pose. The first step of this work consisted in setting up a person detection algorithm in the omnidirectional images. We proposed to extend the conventional approach for human detection in perspective image, based on the Gradient-Oriented Histogram (HOG), in order to adjust it to spherical images. Our approach uses the Riemannian varieties to adapt the gradient calculation for omnidirectional images as well as the spherical gradient for spherical images to generate our omnidirectional image descriptor
Kim, Jae-Seung. "Objective image quality assessment for positron emission tomography : planar (2D) and volumetric (3D) human and model observer studies /." Thesis, Connect to this title online; UW restricted, 2003. http://hdl.handle.net/1773/5836.
Full textChen, Chun-Wei, and 陳俊維. "3D Active Appearance Models for Aligning Faces in 2D Images." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/60979024048802680992.
Full text國立臺灣大學
資訊工程學研究所
96
Perceiving human faces is one of the most important functions for human robot interaction. The active appearance model (AAM) is a statistical approach that models the shape and texture of a target object. According to a number of the existing works, AAM has a great success in modeling human faces. Unfortunately, the traditional AAM framework could fail when the face pose changes as only 2D information is used to model a 3D object. To overcome this limitation, we propose a 3D AAM framework in which a 3D shape model and an appearance model are used to model human faces. Instead of choosing a proper weighting constant to balance the contributions from appearance similarity and the constraint on consistent 2D shape with 3D shape in the existing work, our approach directly matches 2D visual faces with the 3D shape model. No balancing weighting between 2D shape and 3D shape is needed. In addition, only frontal faces are needed for training and non-frontal faces can be aligned successfully. The experimental results with 20 subjects demonstrate the effectiveness of the proposed approach.
Cheng, Yong-Qing. "Acquisition of 3D models from a set of 2D images." 1997. https://scholarworks.umass.edu/dissertations/AAI9809318.
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