Relevant bibliographies by topics / 3D ultrasound localization icroscopy

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic '3D ultrasound localization icroscopy'

Author: Grafiati
Published: 21 December 2024

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Journal articles on the topic "3D ultrasound localization icroscopy"

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Krause, Cassandra, Daniel Wulff, and Floris Ernst. "Target Tracking in 4D Ultrasound using Localization Networks." Current Directions in Biomedical Engineering 10, no. 2 (September 14, 2024): 29–32. http://dx.doi.org/10.1515/cdbme-2024-1059.

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Abstract In radiation therapy, breathing and other influences cause a constant movement of the tissue to be irradiated. Thus, a continuous position control is required which could be handled by the usage of 3D ultrasound imaging. For this purpose, two approaches for target tracking in 3D ultrasound (US) sequences of the liver are analyzed in this study. Therefore, an image-by-image localization of the target is performed using a deep localization network. A singletarget and a multiple-target approach are investigated where deep localization networks are trained for locating one specific and multiple specific targets, respectively. Training the networks and evaluating the tracking algorithm is performed on the basis of a labeled 3D US liver data set in 2-fold crossvalidation experiments. The single-target and multiple-target approaches performed comparable with a mean tracking error of 2.28±1.20mm and 2.23±1.28 mm, respectively. The proposed tracking algorithm is real-time capable with a mean runtime per 3D ultrasound image of 68ms.
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Provost, Jean. "Dynamic ultrasound localization microscopy." Journal of the Acoustical Society of America 153, no. 3_supplement (March 1, 2023): A28. http://dx.doi.org/10.1121/10.0018037.

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Ultrasound localization microscopy (ULM) can map the vasculature at large depth with unprecedented resolution by localizing millions of injected microbubbles in hundreds of thousands of images acquired over a few minutes. The current state of the art in ULM is to use low concentrations to achieve the best possible spatial resolution without providing temporal information, which limits the development of functional biomarkers such as pulsality or the imaging of moving organs like the heart. In this work, we will present dynamic ultrasound localization microscopy (DULM), which enables the generation of dynamic images of the vasculature of periodic phenomena by using a combination of enhanced image formation and processing techniques to drastically increase the number of microbubbles that can be detected in each image. Specifically, we will describe how the detection of microbubbles directly in space time along with novel aberration correction algorithms and a motion-invariant Lagrangian beamforming approach can be used to increase the concentration of microbubbles 5-fold with a limited degradation in resolution. Examples of application for the mapping of pulsatility in the brain and the dynamics of the intramyocardial blood flow in 2D + t and 3D + t will be shown.
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Chinnaiyan, Prakash, Wolfgang Tomé, Rakesh Patel, Rick Chappell, and Mark Ritter. "3D-Ultrasound Guided Radiation Therapy in the Post-Prostatectomy Setting." Technology in Cancer Research & Treatment 2, no. 5 (October 2003): 455–58. http://dx.doi.org/10.1177/153303460300200511.

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Daily transabdominal ultrasound-directed localization has proven valuable in correcting for setup error and organ motion in the treatment of prostate cancer with three-dimensional conformal radiation therapy (3DCRT). The present study sought to determine whether this trans-abdominal ultrasound technology could also be reliably applied in the post-operative adjuvant or salvage setting to improve the reproducibility of coverage of the intended volumes and to enhance conformal avoidance of adjacent normal structures. Sixteen consecutive patients who received external beam radiotherapy underwent daily localization using an optically guided 3D-ultrasound target localization system (SonArray™, Zmed, Inc., Ashland, MA). Six of the above patients were treated in a post-prostatectomy setting, either adjuvantly or for salvage, while the remaining 10 with intact prostates were treated definitively. Because the bladder neck generally approximates the postoperative prostatic fossa, it was used during ultrasound localization as the primary reference structure for the post-prostatectomy patients. For patients treated definitively, the prostate was the primary reference structure. Daily shifts were recorded and port films were taken weekly immediately after ultrasound-based repositioning. By comparing port films taken after ultrasound localization, which evaluates for both set-up error and internal shift, with the original digitally reconstructed radiographs (DRRs), which represents a zero clinical set-up error situation, the degree of variability in organ position was determined. The average absolute, ultrasound-based shifts from the clinical set-up position in the anterior/posterior, lateral, and cranial/caudal directions for the post-prostatectomy patients were 5 ± 4 mm SD, 3 ± 3 mm SD, and 3 ± 4 mm SD over the entire course of treatment, respectively. The average vector length shift was 8 ± 4 mm SD. For patients treated with an intact prostate, the analogous average absolute shifts in the anterior/posterior, lateral, and cranial/caudal directions were 4 ± 3 mm SD, 4 ± 3 mm SD, and 4 ± 3 mm SD over the entire course of treatment. The average vector length shift was 7 ± 4 mm SD. Vector length shifts representing interfraction internal motion were estimated by comparing post-ultrasound port films with DRRs. These were 5 ± 3 mm SD and 4 ± 4mm SD for post-prostatectomy and intact prostate patients, respectively. These ultrasound-based displacements were not statistically different in patients with an intact prostate versus patients post-prostatectomy (p > 0.1). In conclusion, daily transabdominal 3D-ultrasound localization proved to be a clinically feasible method of correcting for set-up and internal motion displacements. The bladder neck, which serves as an adequate localization reference structure for the prostatic fossa, could be readily ultrasound imaged and repositioned as necessary. Daily internal motion errors that would have occurred if only pre-treatment port films were used were similar in magnitude to those observed for the patients with intact prostates and were of sufficient magnitude to support the use of daily pre-treatment ultrasound localization in the post-prostatectomy setting.
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Bandaru, Raja Sekhar, Anders Sørnes, Jan D'hooge, and Eigil Samset. "2066135 3D Localization of Specular Reflections Using Volumetric Ultrasound." Ultrasound in Medicine & Biology 41, no. 4 (April 2015): S56. http://dx.doi.org/10.1016/j.ultrasmedbio.2014.12.250.

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Zhong, Chunyan, Yanli Guo, Haiyun Huang, Liwen Tan, Yi Wu, and Wenting Wang. "Three-Dimensional Reconstruction of Coronary Arteries and Its Application in Localization of Coronary Artery Segments Corresponding to Myocardial Segments Identified by Transthoracic Echocardiography." Computational and Mathematical Methods in Medicine 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/783939.

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Objectives.To establish 3D models of coronary arteries (CA) and study their application in localization of CA segments identified by Transthoracic Echocardiography (TTE).Methods.Sectional images of the heart collected from the first CVH dataset and contrast CT data were used to establish 3D models of the CA. Virtual dissection was performed on the 3D models to simulate the conventional sections of TTE. Then, we used 2D ultrasound, speckle tracking imaging (STI), and 2D ultrasound plus 3D CA models to diagnose 170 patients and compare the results to coronary angiography (CAG).Results.3D models of CA distinctly displayed both 3D structure and 2D sections of CA. This simulated TTE imaging in any plane and showed the CA segments that corresponded to 17 myocardial segments identified by TTE. The localization accuracy showed a significant difference between 2D ultrasound and 2D ultrasound plus 3D CA model in the severe stenosis group (P<0.05) and in the mild-to-moderate stenosis group (P<0.05).Conclusions.These innovative modeling techniques help clinicians identify the CA segments that correspond to myocardial segments typically shown in TTE sectional images, thereby increasing the accuracy of the TTE-based diagnosis of CHD.
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Yang, Xin, Yuhao Huang, Ruobing Huang, Haoran Dou, Rui Li, Jikuan Qian, Xiaoqiong Huang, et al. "Searching collaborative agents for multi-plane localization in 3D ultrasound." Medical Image Analysis 72 (August 2021): 102119. http://dx.doi.org/10.1016/j.media.2021.102119.

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Liu, Xinyu, Jinhua Yu, Yuanyuan Wang, and Ping Chen. "Automatic localization of the fetal cerebellum on 3D ultrasound volumes." Medical Physics 40, no. 11 (October 10, 2013): 112902. http://dx.doi.org/10.1118/1.4824058.

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Uherčík, Marián, Jan Kybic, Yue Zhao, Christian Cachard, and Hervé Liebgott. "Line filtering for surgical tool localization in 3D ultrasound images." Computers in Biology and Medicine 43, no. 12 (December 2013): 2036–45. http://dx.doi.org/10.1016/j.compbiomed.2013.09.020.

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Yao, Junjie. "Deep-brain imaging with 3D integrated photoacoustic tomography and ultrasound localization microscopy." Journal of the Acoustical Society of America 155, no. 3_Supplement (March 1, 2024): A53. http://dx.doi.org/10.1121/10.0026774.

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Photoacoustic computed tomography (PACT) is a proven technology for imaging hemodynamics in deep brain of small animal models. PACT is inherently compatible with ultrasound (US) imaging, providing complementary contrast mechanisms. While PACT can quantify the brain’s oxygen saturation of hemoglobin (sO2), US imaging can probe the blood flow based on the Doppler effect. Furthermore, by tracking gas-filled microbubbles, ultrasound localization microscopy (ULM) can map the blood flow velocity with sub-diffraction spatial resolution. In this work, we present a 3D deep-brain imaging system that seamlessly integrates PACT and ULM into a single device, 3D-PAULM. Using a low ultrasound frequency of 4 MHz, 3D-PAULM is capable of imaging the whole-brain hemodynamic functions with intact scalp and skull in a totally non-invasive manner. Using 3D-PAULM, we studied the mouse brain functions with ischemic stroke. Multi-spectral PACT, US B-mode imaging, microbubble-enhanced power Doppler (PD), and ULM were performed on the same mouse brain with intrinsic image co-registration. From the multi-modality measurements, we future quantified blood perfusion, sO2, vessel density, and flow velocity of the mouse brain, showing stroke-induced ischemia, hypoxia, and reduced blood flow. We expect that 3D-PAULM can find broad applications in studying deep brain functions on small animal models.
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van der Burgt, Jeroen M. A., Saskia M. Camps, Maria Antico, Gustavo Carneiro, and Davide Fontanarosa. "Arthroscope Localization in 3D Ultrasound Volumes Using Weakly Supervised Deep Learning." Applied Sciences 11, no. 15 (July 25, 2021): 6828. http://dx.doi.org/10.3390/app11156828.

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This work presents an algorithm based on weak supervision to automatically localize an arthroscope on 3D ultrasound (US). The ultimate goal of this application is to combine 3D US with the 2D arthroscope view during knee arthroscopy, to provide the surgeon with a comprehensive view of the surgical site. The implemented algorithm consisted of a weakly supervised neural network, which was trained on 2D US images of different phantoms mimicking the imaging conditions during knee arthroscopy. Image-based classification was performed and the resulting class activation maps were used to localize the arthroscope. The localization performance was evaluated visually by three expert reviewers and by the calculation of objective metrics. Finally, the algorithm was also tested on a human cadaver knee. The algorithm achieved an average classification accuracy of 88.6% on phantom data and 83.3% on cadaver data. The localization of the arthroscope based on the class activation maps was correct in 92–100% of all true positive classifications for both phantom and cadaver data. These results are relevant because they show feasibility of automatic arthroscope localization in 3D US volumes, which is paramount to combining multiple image modalities that are available during knee arthroscopies.
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Dissertations / Theses on the topic "3D ultrasound localization icroscopy"

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Abioui, Mourgues Myriam. "Dévelοppement d'un mοdèle préclinique chez la sοuris éveillée et stratégie thrοmbοlytique ciblée pοur l'AVC ischémique." Electronic Thesis or Diss., Normandie, 2024. http://www.theses.fr/2024NORMC420.

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L’Accident Vasculaire Cérébral (AVC) ischémique, causé par l’obstruction d’une artère cérébrale, est l’une des principales causes de mortalité et d’invalidité dans le monde. Bien que des traitements comme le rtPA et la thrombectomie mécanique existent, seul un faible pourcentage de patients y a accès. Par ailleurs, malgré l’investissement de la recherche, les difficultés à transposer les résultats des modèles animaux aux essais cliniques humains limitent le développement de nouvelles thérapies. Cette thèse présente un modèle d’AVC chez la souris éveillée visant à améliorer la transposabilité des études précliniques. Grâce à l’imagerie ultrasonore fonctionnelle (fUS) et à l’IRM, ce modèle permet une évaluation en temps réel des paramètres hémodynamiques ainsi qu’une analyse de la récupération fonctionnelle après l’ischémie. Nous proposons également un nouvel outil d’évaluation de la connectivité cérébrale post-AVC, apportant des informations sur la récupération cérébrale et la réponse au traitement. L’efficacité du traitement thrombolytique standard, le rtPA, a été testée, et une approche innovante de traitement ciblé a été explorée. Les résultats soulignent le potentiel de ces approches multimodales et thérapeutiques ciblées pour améliorer la prise en charge des AVC ischémiques, ouvrant la voie à de nouvelles perspectives de recherche translationnelle
Ischemic stroke, caused by the obstruction of a cerebral artery, is one of the leading causes of mortality and disability worldwide. Despite the availability of treatments such as rtPA and endovascular thrombectomy, only a small percentage of patients have access to these. Moreover, despite substantial research efforts, challenges in translating results from animal models to human clinical trials limit the development of new therapies. This thesis presents a novel stroke model in awake mice to improve the translatability of preclinical studies. Through the use of functional ultrasound (fUS) and MRI, this model enables real-time assessment of hemodynamic parameters and functional recovery following ischemia. Additionally, we propose a new tool for evaluating post-stroke brain connectivity, providing insights into brain recovery and treatment response. The efficacy of the stantard thrombolytic treatment, rtPA, was evaluated, and an innovative targeted treatment approach was explored. The results underscore the potential of these multimodal imaging approaches and targeted therapies to enhance ischemic stroke management, opening new avenues for translational research
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Uhercik, Marian. "Surgical tools localization in 3D ultrasound images." Phd thesis, INSA de Lyon, 2011. http://tel.archives-ouvertes.fr/tel-00735702.

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This thesis deals with automatic localization of thin surgical tools such as needles or electrodes in 3D ultrasound images. The precise and reliable localization is important for medical interventions such as needle biopsy or electrode insertion into tissue. The reader is introduced to basics of medical ultrasound (US) imaging. The state of the art localization methods are reviewed in the work. Many methods such as Hough transform (HT) or Parallel Integral Projection (PIP) are based on projections. As the existing PIP implementations are relatively slow, we suggest an acceleration by using a multiresolution approach. We propose to use model fitting approach which uses randomized sample consensus (RANSAC) and local optimization. It is a fast method suitable for real-time use and it is robust with respect to the presence of other high-intensity structures in the background. We propose two new shape and appearance models of tool in 3D US images. Tool localization can be improved by exploiting its tubularity. We propose a tool model which uses line filtering and we incorporated it into the model fitting scheme. The robustness of such localization algorithm is improved at the expense of additional time for pre-processing. The real-time localization using the shape model is demonstrated by implementation on the 3D US scanner Ultrasonix RP. All proposed methods were tested on simulated data, phantom US data (a replacement for a tissue) and real tissue US data of breast with biopsy needle. The proposed methods had comparable accuracy and the lower number of failures than the state of the art projection based methods.
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Heiles, Baptiste. "Microscopie par Localisation Ultrasonore en 3D." Thesis, Paris Sciences et Lettres (ComUE), 2019. https://pastel.archives-ouvertes.fr/tel-02953081.

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La microscopie par localization ultrasonore a montré qu’il était possible de s’affranchir du compromis entre la penetration et la resolution en échographie grâce aux ultrasons ultrarapides et à l’utilisation d’agents de contraste. Cependant, cette technique sera difficilement transposable dans un environment clinique car elle implique : 1. de longs temps d’acquisitions, 2. un champ de vue limité à un plan, 3. l’impossibilité de corriger les mouvements hors plan, 4. des quantités de données importantes et 5. des temps de calculs extrêmement longs. En développant cette technique en 3 dimensions, il sera possible d’explorer des volumes anatomiques entiers en quelques minutes d’acquisition afin de voir la microvasculature mais aussi d’imager des organes soumis au mouvement (comme cela est le cas pour l’imagerie d’un patient).L’objectif de cette thèse a été de démontrer qu’il était possible de faire de la microscopie par localization ultrasonore en 3D sur des larges volumes, et de montrer son potentiel in vitro et in vivo. Le point de depart a été de developer des nouvelles techniques de localisation de particules, ce qui a permis de diviser par 300 le temps de calcul en 2D et de fournir une imagerie de meilleure qualité. Grâce à leur implémentation en 3 dimensions, elles ont rendu possible la microscopie par localization ultrasonore en 3D dans des temps réduits. Ensuite, nous avons créé des sequences d’imagerie 4D spécifiques pour la microscopie en 3D et montré qu’il était possible d’imager avec une résolution sub longueur d’onde un fantôme de canaux microfluidiques 3D. Ce fantôme a été développé spécifiquement pour démontrer la faisabilité de la technique en 3D. Après avoir éprouvé notre technique in vitro, nous l’avons appliquée in vivo sur le cerveau de rat et démontré qu’il était possible d’avoir accès à la vasculature ainsi qu’aux flux sanguins à une échelle de quelques microns. Une étape supplémentaire a été ajoutée dans le framework de l’algorithme afin de corriger le mouvement en 3 dimensions et de recaler des volumes superrésolus entre eux afin de produire le premier volume d’un cerveau de rat entier (bulbe olfactif, cervelet et lobes principaux).Le développement de la microscopie par localisation ultrasonore en 3D ouvre la voie vers une imagerie préclinique in vivo de meilleure qualité et plus rapide. Grâce aux innovations technologiques actuelles, l’utilisation de cette technique en recherche se fera de plus en plus fréquente jusqu’à être adoptée en clinique
Ultrasound Localization Microscopy has demonstrated the ability to overcome the penetration/resolution conundrum in ultrasound imaging thanks to high frame rate imaging and contrast agents. However, this approach will fall short in its clinical translation if its main disadvantages aren’t addressed: 1- long time of acquisition 2- limited two dimensional field of view 3- motion artifacts 4-data overdose and 5- data processing times. Developing 3D ULM will allow to explore entire volumes within a few minutes of acquisition, giving access to all blood vessels down to micrometer size and imaging moving organs (i.e. a patient in a clinical setting).The objective of this thesis was to perform, for the first time, volumetric ultrasound localization microscopy and unveil its potential in-vitro and in-vivo. For this purpose, I first developed new post-processing techniques, reducing 2D data processing times by a factor of 300, allowing implementation of ULM on 3D data and increasing image quality. Then, I implemented new ultrasound sequences and demonstrated that sub-wavelength features could be resolved in a tailor made wall-less phantom. I then demonstrated that 3D imaging of the rat brain microvasculature with blood flow velocimetry was achievable with micrometric resolution, and implemented 3D motion correction and image registration to provide whole brain imaging.This new tool was used to investigate both the anatomy and the vascularization mechanisms in the brain. Making the transition from 2D ULM to 3D ULM paves the way towards better imaging of in vivo organs in the rat. Thanks to technological improvements 3D ULM will spread fast in research imaging and reach all the way to clinical care
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Zhao, Yue. "Biopsy needles localization and tracking methods in 3d medical ultrasound with ROI-RANSAC-KALMAN." Thesis, Lyon, INSA, 2014. http://www.theses.fr/2014ISAL0015/document.

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Dans les examens médicaux et les actes de thérapie, les techniques minimalement invasives sont de plus en plus utilisées. Des instruments comme des aiguilles de biopsie, ou des électrodes sont utilisés pour extraire des échantillons de cellules ou pour effectuer des traitements. Afin de réduire les traumatismes et de faciliter le suivi visuelle de ces interventions, des systèmes d’assistance par imagerie médicale, comme par exemple, par l’échographie 2D, sont utilisés dans la procédure chirurgicale. Nous proposons d’utiliser l’échographie 3D pour faciliter la visualisation de l’aiguille, mais en raison de l’aspect bruité de l’image ultrasonore (US) et la grande quantité de données d’un volume 3D, il est difficile de trouver l’aiguille de biopsie avec précision et de suivre sa position en temps réel. Afin de résoudre les deux principaux problèmes ci-dessus, nous avons proposé une méthode basée sur un algorithme RANSAC et un filtre de Kalman. De même l’étude est limitée à une région d’intérêt (ROI) pour obtenir une localisation robuste et le suivi de la position de l’aiguille de biopsie en temps réel. La méthode ROI-RK se compose de deux étapes: l’étape d’initialisation et l’étape de suivi. Dans la première étape, une stratégie d’initialisation d’une ROI en utilisant le filtrage de ligne à base de matrice de Hesse est mise en œuvre. Cette étape permet de réduire efficacement le bruit de granularité du volume US, et de renforcer les structures linéaires telles que des aiguilles de biopsie. Dans la deuxième étape, après l’initialisation de la ROI, un cycle de suivi commence. L’algorithme RK localise et suit l’aiguille de biopsie dans une situation dynamique. L’algorithme RANSAC est utilisé pour estimer la position des micro-outils et le filtrage de Kalman permet de mettre à jour la région d’intérêt et de corriger la localisation de l’aiguille. Une stratégie d’estimation de mouvement est également appliquée pour estimer la vitesse d’insertion de l’aiguille de biopsie. Des volumes 3D US avec un fond inhomogène ont été simulés pour vérifier les performances de la méthode ROI-RK. La méthode a été testée dans des conditions variables, telles que l’orientation d’insertion de l’aiguille par rapport à l’axe de la sonde et le niveau de contraste (CR). La précision de la localisation est de moins de 1 mm, quelle que soit la direction d’insertion de l’aiguille. Ce n’est que lorsque le CR est très faible que la méthode proposée peut échouer dans le suivi d’une structure incomplète de l’aiguille. Une autre méthode, utilisant l’algorithme RANSAC avec apprentissage automatique a été proposée. Cette méthode vise à classer les voxels en se basant non seulement sur l’intensité, mais aussi sur les caractéristiques de la structure de l’aiguille de biopsie. Les résultats des simulations montrent que l’algorithme RANSAC avec apprentissage automatique peut séparer les voxels de l’aiguille et les voxels de tissu de fond avec un CR faible
In medical examinations and surgeries, minimally invasive technologies are getting used more and more often. Some specially designed surgical instruments, like biopsy needles, or electrodes are operated by radiologists or robotic systems and inserted in human’s body for extracting cell samples or delivering radiation therapy. To reduce the risk of tissue injury and facilitate the visual tracking, some medical vision assistance systems, as for example, ultrasound (US) systems can be used during the surgical procedure. We have proposed to use the 3D US to facilitate the visualization of the biopsy needle, however, due to the strong speckle noise of US images and the large calculation load involved as soon as 3D data are involved, it is a challenge to locate the biopsy needle accurately and to track its position in real time in 3D US. In order to solve the two main problems above, we propose a method based on the RANSAC algorithm and Kalman filter. In this method, a region of interest (ROI) has been limited to robustly localize and track the position of the biopsy needle in real time. The ROI-RK method consists of two steps: the initialization step and the tracking step. In the first step, a ROI initialization strategy using Hessian based line filter measurement is implemented. This step can efficiently reduce the speckle noise of the ultrasound volume, and enhance line-like structures as biopsy needles. In the second step, after the ROI is initialized, a tracking loop begins. The RK algorithm can robustly localize and track the biopsy needles in a dynamic situation. The RANSAC algorithm is used to estimate the position of the micro-tools and the Kalman filter helps to update the ROI and auto-correct the needle localization result. Because the ROI-RK method is involved in a dynamic situation, a motion estimation strategy is also implemented to estimate the insertion speed of the biopsy needle. 3D US volumes with inhomogeneous background have been simulated to evaluate the performance of the ROI-RK method. The method has been tested under different conditions, such as insertion orientations angles, and contrast ratio (CR). The localization accuracy is within 1 mm no matter what the insertion direction is. Only when the CR is very low, the proposed method could fail to track because of an incomplete ultrasound imaging of the needle. Another methodology, i.e. RANSAC with machine learning (ML) algorithm has been presented. This method aims at classifying the voxels not only depending on their intensities, but also using some structure features of the biopsy needle. The simulation results show that the RANSAC with ML algorithm can separate the needle voxels and background tissue voxels with low CR
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Zarader, Pierre. "Transcranial ultrasound tracking of a neurosurgical microrobot." Electronic Thesis or Diss., Sorbonne université, 2024. http://www.theses.fr/2024SORUS054.

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Dans l'objectif de traiter les tumeurs cérébrales difficilement accessibles avec les outils chirugicaux actuels, Robeauté développe un microrobot innovant dans l'objectif de naviguer dans les zones cérébrales profondes avec un minimum d'invasivité. L'objectif de cette thèse a été de développer et de valider un système de suivi ultrasonore transcrânien du microrobot afin de pouvoir implémenter des commandes robotiques et garantir ainsi la sûreté et l'efficacité de l'intervention.L'approche proposée consiste à placer trois émetteurs ultrasonores sur la tête du patient, et à embarquer un récepteur ultrasonore sur le microrobot. En connaissant la vitesse du son dans les tissus biologiques et l'épaisseur de crâne traversée, il est possible d'estimer les distances entre les émetteurs et le récepteur par mesure de temps de vol, et d'en déduire sa position 3D par trilatération. Une preuve de concept a d'abord été réalisée à travers un modèle de crâne d'épaisseur constante, démontrant une précision de localisation submillimétrique. Pour se placer dans un contexte clinique, le système a ensuite été évalué à travers un modèle de calvaria dont l'épaisseur et la vitesse du son en face de chaque émetteur ont été déduites par tomodensitométrie. Le système a démontré une précision de localisation moyenne de 1.5 mm, soit une dégradation de la précision d'1 mm comparée à celle du suivi à travers le modèle de crâne d'épaisseur constante, expliquée par l'incertitude apportée par l'épaisseur hétérogène de la calvaria. Enfin, trois tests pré-cliniques, sans possibilité d'évaluer l'erreur de localisation, ont été réalisés : (i) un test post-mortem sur un humain, (ii) un test post-mortem sur une brebis, (iii) et un test in vivo sur une brebis.De futures pistes d'amélioration du système de suivi ont été proposées, telles que (i) l'utilisation de simulation de propagation ultrasonore transcrânienne basée sur une tomodensitométrie pour la prise en compte des hétérogénéités du crâne, (ii) la miniaturisation du capteur ultrasonore embarqué sur le microrobot, (iii) ainsi que l'intégration d'une imagerie ultrasonore pour la visualisation de la vascularisation locale autour du microrobot, permettant ainsi de réduire le risque de lésions et de détecter d'éventuelles angiogenèses pathologiques
With the aim of treating brain tumors difficult to access with current surgical tools, Robeauté is developing an innovative microrobot to navigate deep brain areas with minimal invasiveness. The aim of this thesis was to develop and validate a transcranial ultrasound-based tracking system for the microrobot, in order to be able to implement robotic commands and thus guarantee both the safety and the effectiveness of the intervention.The proposed approach consists in positioning three ultrasound emitters on the patient's head, and embedding an ultrasound receiver on the microrobot. Knowing the speed of sound in biological tissue and the skull thickness crossed, it is possible to estimate the distances from the emitters to the receiver by time-of-flight measurements, and to deduce its 3D position by trilateration. A proof of concept was first carried out using a skull phantom of constant thickness, demonstrating submillimeter localization accuracy. The system was then evaluated using a calvaria phantom whose thickness and speed of sound in front of each emitter were deduced by CT scan. The system demonstrated an mean localization accuracy of 1.5 mm, i.e. a degradation in accuracy of 1 mm compared with the tracking through the skull phantom of constant thickness, explained by the uncertainty brought by the heterogeneous shape of the calvaria. Finally, three preclinical tests, without the possibility of assessing localization error, were carried out: (i) a post-mortem test on a human, (ii) a post-mortem test on a ewe, (iii) and an in vivo test on a ewe.Further improvements to the tracking system have been proposed, such as (i) the use of CT scan-based transcranial ultrasound propagation simulation to take account of skull heterogeneities, (ii) the miniaturization of the ultrasound sensor embedded in the microrobot, (iii) as well as the integration of ultrasound imaging to visualize local vascularization around the microrobot, thereby reducing the risk of lesions and detecting possible pathological angiogenesis
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Book chapters on the topic "3D ultrasound localization icroscopy"

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Novotny, Paul M., Jeremy W. Cannon, and Robert D. Howe. "Tool Localization in 3D Ultrasound Images." In Lecture Notes in Computer Science, 969–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39903-2_127.

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Yeung, Pak-Hei, Moska Aliasi, Monique Haak, Weidi Xie, and Ana I. L. Namburete. "Adaptive 3D Localization of 2D Freehand Ultrasound Brain Images." In Lecture Notes in Computer Science, 207–17. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-16440-8_20.

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Sun, Shih-Yu, Matthew Gilbertson, and Brian W. Anthony. "Probe Localization for Freehand 3D Ultrasound by Tracking Skin Features." In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014, 365–72. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10470-6_46.

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Huang, Yuhao, Xin Yang, Rui Li, Jikuan Qian, Xiaoqiong Huang, Wenlong Shi, Haoran Dou, et al. "Searching Collaborative Agents for Multi-plane Localization in 3D Ultrasound." In Medical Image Computing and Computer Assisted Intervention – MICCAI 2020, 553–62. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59716-0_53.

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Mohareri, Omid, Mahdi Ramezani, Troy Adebar, Purang Abolmaesumi, and Septimiu Salcudean. "Automatic Detection and Localization of da Vinci Tool Tips in 3D Ultrasound." In Information Processing in Computer-Assisted Interventions, 22–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30618-1_3.

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Mwikirize, Cosmas, John L. Nosher, and Ilker Hacihaliloglu. "Local Phase-Based Learning for Needle Detection and Localization in 3D Ultrasound." In Lecture Notes in Computer Science, 108–15. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67543-5_10.

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Dou, Haoran, Xin Yang, Jikuan Qian, Wufeng Xue, Hao Qin, Xu Wang, Lequan Yu, et al. "Agent with Warm Start and Active Termination for Plane Localization in 3D Ultrasound." In Lecture Notes in Computer Science, 290–98. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32254-0_33.

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Zou, Yuxin, Haoran Dou, Yuhao Huang, Xin Yang, Jikuan Qian, Chaojiong Zhen, Xiaodan Ji, et al. "Agent with Tangent-Based Formulation and Anatomical Perception for Standard Plane Localization in 3D Ultrasound." In Lecture Notes in Computer Science, 300–309. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-16440-8_29.

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Xu, Rong, Jun Ohya, Bo Zhang, Yoshinobu Sato, and Masakatsu G. Fujie. "A Flexible Surgical Tool Localization Using a 3D Ultrasound Calibration System for Fetoscopic Tracheal Occlusion (FETO)." In Clinical Image-Based Procedures. From Planning to Intervention, 17–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38079-2_3.

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Chen, Alvin I., Max L. Balter, Timothy J. Maguire, and Martin L. Yarmush. "3D Near Infrared and Ultrasound Imaging of Peripheral Blood Vessels for Real-Time Localization and Needle Guidance." In Lecture Notes in Computer Science, 388–96. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46726-9_45.

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Conference papers on the topic "3D ultrasound localization icroscopy"

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Dencks, Stefanie, Nico Oblisz, Thomas Lisson, and Georg Schmitz. "Achievable Localization Precision of Clinical 3D Ultrasound Localization Microscopy (ULM)." In 2022 IEEE International Ultrasonics Symposium (IUS). IEEE, 2022. http://dx.doi.org/10.1109/ius54386.2022.9957160.

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Shahin, O., V. Martens, A. Besirevic, M. Kleemann, and A. Schlaefer. "Localization of liver tumors in freehand 3D laparoscopic ultrasound." In SPIE Medical Imaging, edited by David R. Holmes III and Kenneth H. Wong. SPIE, 2012. http://dx.doi.org/10.1117/12.912375.

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Barva, Martin, Jan Kybic, Jean-Martial Mari, Christian Cachard, and Vaclav Hlavac. "Automatic localization of curvilinear object in 3D ultrasound images." In Medical Imaging, edited by William F. Walker and Stanislav Y. Emelianov. SPIE, 2005. http://dx.doi.org/10.1117/12.594763.

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Schmauder, Michael, Steffen Zeiler, C. M. Gross, Juergen Waigand, and Reinhold Orglmeister. "Automated 3D-stent localization from intravascular ultrasound image sequences." In Medical Imaging 2000, edited by Kenneth M. Hanson. SPIE, 2000. http://dx.doi.org/10.1117/12.387656.

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Younes, Hatem, Sandrine Voros, and Jocelyne Troccaz. "Automatic needle localization in 3D ultrasound images for brachytherapy." In 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018). IEEE, 2018. http://dx.doi.org/10.1109/isbi.2018.8363787.

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Wang, Bingxue, Jipeng Yan, Kai Riemer, Matthieu Toulemonde, Joseph Hansen-Shearer, and Meng-Xing Tang. "Comparison of localization methods for 3D Super-Resolution Ultrasound Imaging." In 2022 IEEE International Ultrasonics Symposium (IUS). IEEE, 2022. http://dx.doi.org/10.1109/ius54386.2022.9957144.

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Han, Wenzhao, Yuting Zhang, Yachuan Zhao, Anguo Luo, and Bo Peng. "3D U-Net3+ Based Microbubble Filtering for Ultrasound Localization Microscopy." In 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2023. http://dx.doi.org/10.1109/smc53992.2023.10394576.

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Wu Qiu, Mingyue Ding, and Ming Yuchi. "Electrode Localization in 3D Ultrasound Images Using 3D Phase Grouping and Randomized Hough Transform." In 2010 Fourth International Conference on Genetic and Evolutionary Computing (ICGEC 2010). IEEE, 2010. http://dx.doi.org/10.1109/icgec.2010.57.

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Sugimoto, Masanori, Noriyoshi Kanie, Shigeki Nakamura, and Hiromichi Hashizume. "An accurate 3D localization technique using a single camera and ultrasound." In 2012 International Conference on Indoor Positioning and Indoor Navigation (IPIN). IEEE, 2012. http://dx.doi.org/10.1109/ipin.2012.6418874.

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Pourtaherian, Arash, Nenad Mihajlovic, Farhad Ghazvinian Zanjani, Svitlana Zinger, Gary C. Ng, Hendrikus H. M. Korsten, and Peter H. N. De With. "Localization of Partially Visible Needles in 3D Ultrasound Using Dilated CNNs." In 2018 IEEE International Ultrasonics Symposium (IUS). IEEE, 2018. http://dx.doi.org/10.1109/ultsym.2018.8579986.

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