Добірка наукової літератури з теми "Image volumétrique"
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Статті в журналах з теми "Image volumétrique"
Petitpas, Laurent, and Frédérick Van Meer. "L’utilisation de fichiers 3D pour la création d’un clone virtuel." Revue d'Orthopédie Dento-Faciale 55, no. 1 (February 2021): 53–72. http://dx.doi.org/10.1051/odf/2021005.
Повний текст джерелаKim, Changwan, Seong-Il Bin, Bum-Sik Lee, Won-Joon Cho, June-Goo Lee, Gi-Woon Yoon, and Jong-Min Kim. "Évaluation volumétrique de l’extrusion dans les déchirures des racines postérieures du ménisque médial par segmentation semi-automatique des images IRM 3 teslas." Revue de Chirurgie Orthopédique et Traumatologique 106, no. 5 (September 2020): 550. http://dx.doi.org/10.1016/j.rcot.2020.06.003.
Повний текст джерелаДисертації з теми "Image volumétrique"
Hatvani, Janka. "Amélioration des images médicales à l'aide de techniques d'apprentissage profond et de factorisation tensorielle." Electronic Thesis or Diss., Toulouse 3, 2021. http://www.theses.fr/2021TOU30304.
Повний текст джерелаThe resolution of dental cone beam computed tomography (CBCT) images is imited by detector geometry, sensitivity, patient movement, the reconstruction technique and the need to minimize radiation dose. The corresponding image degradation model assumes that the CBCT image is a blurred (with a point spread function, PSF), downsampled, noisy version of a high resolution image. The quality of the image is crucial for precise diagnosis and treatment planning. The methods proposed in this thesis aim to give a solution for the single image super-resolution (SISR) problem. The algorithms were evaluated on dental CBCT and corresponding highresolution (and high radiation-dose) µCT image pairs of extracted teeth. I have designed a deep learning framework for the SISR problem, applied to CBCT slices. I have tested the U-net and subpixel neural networks, which both improved the PSNR by 21-22 dB, and the Dice coe_cient of the canal segmentation by 1-2.2%, more significantly in the medically critical apical region. I have designed an algorithm for the 3D SISR problem, using the canonical polyadic decomposition of tensors. This implementation conserves the 3D structure of the volume, integrating the factorization-based denoising, deblurring with a known PSF, and upsampling of the image in a lightweight algorithm with a low number of parameters. It outperforms the state-of-the-art 3D reconstruction-based algorithms with two orders of magnitude faster run-time and provides similar PSNR (improvement of 1.2-1.5 dB) and segmentation metrics (Dice coe_cient increased on average to 0.89 and 0.90). Thesis II b: I have implemented a joint alternating recovery of the unknown PSF parameters and of the high-resolution 3D image using CPD-SISR. The algorithm was compared to a state-of-the-art 3D reconstruction-based algorithm, combined with the proposed alternating PSF-optimization. The two algorithms have shown similar improvement in PSNR, but CPD-SISR-blind converged roughly 40 times faster, under 6 minutes both in simulation and on experimental dental computed tomography data. I have proposed a solution for the 3D SISR problem using the Tucker decomposition (TD-SISR). The denoising step is realized _rst by TD in order to mitigate the ill-posedness of the subsequent deconvolution. Compared to CPDSISR the algorithm runs ten times faster. Depending on the amount of noise, higher PSNR (0.3 - 3.5 dB), SSI (0.58 - 2.43%) and segmentation values (Dice coefficient, 2% improvement) were measured. The parameters in TD-SISR are familiar from 2D SVD-based algorithms, so their tuning is easier compared to CPD-SISR
Azizian, Kalkhoran Mohammad. "Design and development of a universal handheld probe for optoacoustic-ultrasonic 3D imaging." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSEI027/document.
Повний текст джерелаWhen the interest is in multiscale and multipurpose imaging, there exists such a will in integrating multi-modalilties into a synergistic paradigm in order to leverage the diagnostic values of the interrogating agents. Employing multiple wavelengths radiation, optoacoustic imaging benefits from the optical contrast to specifically resolve molecular structure of tissue in a non-invasive manner. Hybridizing optoacoustic and ultrasound imaging comes with the promises of delivering the complementary morphological, functional and metabolic information of the tissue. This dissertation is mainly devoted to the design and characterization of a hybridized universal handheld probe for optoacoustic ultrasound volumetric imaging and developing adaptive reconstruction algorithms toward the physical requirements of the designed system. The distinguishing features of this dissertation are the introduction of a new geometry for optoacoustic ultrasonic handheld probe and systematic assessments based on pre and post reconstruction methods. To avoid the biased interpretation, a de facto performance assessment being capable of evaluating the potentials of the designed probe in an unbiased manner must be practiced. The aforementioned features establish a framework for characterization of the imaging system performance in an accurate manner. Moreover, it allows further task performance optimization as well. Correspondingly, two advanced reconstruction algorithms have been elaborated towards the requirement of the designed optoacoustic-ultrasound (OPUS) imaging system in order to maximize its ability to produce images with homogeneous contrast and resolution over the entire volume of interest. This interest is mainly due to the fact that the medical data analysis pipeline is often carried out in challenging conditions, since one has to deal with noise, low contrast, limited projections and undesirable transformations operated by the acquisition system. The presented thesis shows how reconstruction artifacts can be reduced by compensating for the detecting aperture properties and alleviate artifacts due to sparse angular sampling. In pursuit of transferring this methodology to clinic and validating the theoretical results, a synthetic imaging platform was developed. Using the measurement system, the evolution of a novel sparse annular geometry and its dynamics has been investigated and a proof of concept was demonstrated via experimental measurement with the intention of benchmarking progress
Barateau, Anaïs. "Calcul de dose à partir d'images CBCT et IRM en radiothérapie externe." Thesis, Rennes 1, 2019. http://www.theses.fr/2019REN1B064.
Повний текст джерелаStandard external beam radiotherapy is based on a planning computed tomography (CT) scan. This CT provides electron densities required for dose calculation. 3D imaging such as cone beam CT (CBCT), MV-CT or magnetic resonance imaging (MRI), are acquired just before irradiation for target volume registration. These images could be used to quantify dosimetric impact of anatomical variations occurring during the treatment course. The objective of the thesis was to develop, evaluate and compare CBCT-based and MRI-based dose calculation methods, in a dose-guided adaptive radiotherapy perspective. For head-and-neck CBCT-based dose calculation, a deep learning method was compared to three other methods from literature. For prostate MRI-based dose calculation, nine methods including an atlas-based, a patch-based and deep learning methods with different architectures were compared. Moreover, dosimetric benefits of adaptive radiotherapy strategies (offline for head-and-neck and plan treatment library for cervix) were evaluated. To generate pseudo-CT from CBCT or MRI, deep learning methods are promising, since they are fast and accurate. These methods can be used for a dose monitoring during treatment course in an adaptive radiotherapy process
Boydev, Christine. "Segmentation automatique des images de tomographie conique pour la radiothérapie de la prostate." Thesis, Valenciennes, 2015. http://www.theses.fr/2015VALE0030/document.
Повний текст джерелаThe use of CBCT imaging for image-guided radiation therapy (IGRT), and beyond that, image-guided adaptive radiation therapy (IGART), in the context of prostate cancer is challenging due to the poor contrast and high noise in pelvic CBCT images. The principal aim of the thesis is to provide methodological contributions for automatic intra-patient image registration between the planning CT scan and the treatment CBCT scan. The first part of our contributions concerns the development of a CBCT-based prostate setup correction strategy using CT-to-CBCT rigid registration (RR). We established a comparison between different RR algorithms: (a) global RR, (b) bony RR, and (c) bony RR refined by a local RR using the prostate CTV in the CT scan expanded with 1- to-20-mm varying margins. A comprehensive statistical analysis of the quantitative and qualitative results was carried out using the whole dataset composed of 115 daily CBCT scans and 10 planning CT scans from 10 prostate cancer patients. We also defined a novel practical method to automatically estimate rectal distension occurred in the vicinity of the prostate between the CT and the CBCT scans. Using our measure of rectal distension, we evaluated the impact of rectal distension on the quality of local RR and we provided a way to predict registration failure. On this basis, we derived recommendations for clinical practice for the use of automatic RR for prostate localization on CBCT scans. The second part of the thesis provides a methodological development of a new joint segmentation and deformable registration framework. To deal with the poor contrast-to-noise ratio in CBCT images likely to misguide registration, we conceived a new metric (or enery) which included two terms: a global similarity term (the normalized cross correlation (NCC) was used, but any other one could be used instead) and a segmentation term based on a localized adaptation of the piecewise-constant region-based model of Chan-Vese using an evolving contour in the CBCT image. Our principal aim was to improve the accuracy of the registration compared with an ordinary NCC metric. Our registration algorithm is fully automatic and takes as inputs (1) the planning CT image, (2) the daily CBCT image and (3) the binary image associated with the CT image and corresponding to the organ of interest we want to segment in the CBCT image in the course of the registration process
Hadj-Hamou, Mehdi. "Au-delà de la volumétrie en morphométrie basée sur les déformations : application au dimorphisme sexuel durant l'adolescence." Thesis, Université Côte d'Azur (ComUE), 2016. http://www.theses.fr/2016AZUR4141/document.
Повний текст джерелаAnalysing the progression of brain morphological changes in time series of images is an important topic in neuroimaging. Although the development of longitudinal databases has helped reducing the inter-individual variability, there still exist numerous biases that need to be avoided when capturing longitudinal evolutions. Moreover, when the intra-subject changes are very small with respect to the inter-subject variability it is crucial to know if the available methods can capture the longitudinal change with no bias. In most of the studies, these longitudinal changes are limited to scalar volumetric changes in order to ease their analysis. However, one can observe that brain changes are not limited to volumetry. In this multivariate case, the interpretation is more difficult. This thesis addresses these problems along three main axes. First, we propose a longitudinal Deformation-based Morphometry processing pipeline to robustly estimate the longitudinal changes. We detail the whole sequencing of the processing steps as they are key to avoid adding bias. In addition to this contribution we integrate a modification to the non-linear registration algorithm by masking the similarity term while keeping the symmetry of the formulation. This change increases the robustness of the results with respect to intensity artifacts located in the brain boundaries and leads to increased sensitivity of the statistical study on the longitudinal deformations. The proposed processing pipeline is based on freely available software and tools so that it is fully reproducible
Vallaeys, Karen. "Exploitation des données endodontiques en tomographie volumique : de la microtomographie in vitro à la scanographie in vivo." Thesis, Brest, 2017. http://www.theses.fr/2017BRES0144/document.
Повний текст джерелаCone Beam Computerized Tomography (CBCT) is a highly relevant three-dimensional imaging technology for use in dentistry. Our work aims to show its interests and specific applications in endodontics. After having redefined the possible deleterious per and post-operative consequences of endodontic treatments and explained the principles of CBCT, we first explore the effects of in vitro canal preparation, using high resolution microtomography and then, in a second time, the problematic and the interests of the creation of reliable and precise three-dimensional reconstructions. This last part deals with the notions of CBCT image processing before explaining the approach adopted to develop a three-dimensional classification of endodontic periapical lesions in digital and physical form
Fetita, Catalin Iulian. "Analyse morphofonctionnelle des voies aériennes en TDM spiralée volumique." Paris 5, 2000. http://www.theses.fr/2000PA055021.
Повний текст джерелаRacicot, Marc. "Multi-view 3D reconstruction using virtual cameras." Thèse, 2015. http://hdl.handle.net/1866/12572.
Повний текст джерелаThis master concentrates on the reconstruction of a 3D model from multiple images. The 3D model is built with a hierarchical representation of voxels using an octree. A cube surrounding the object is calculated from the camera's positions. This cube contains all the voxels and it defines the position of the virtual cameras. The 3d model is initialized by a visual hull that is based on the uniform color of the images’ background. This visual hull is used to pre-carve the 3D model. Then a cost is calculated to evaluate the quality of each voxel as being on the surface of the object. This cost takes into account the similarity of the pixels from each images associated to a virtual camera. Finally a surface is calculated for each virtual camera using the SGM method that is based on the voxel cost. The SGM method takes the surrounding voxels into account when calculating the depth and this master presents a variation to this method where we take the previously excluded voxels into account. The excluded voxels coming from the initialization step or from the carving done by another virtual camera. The resulting surface is used to carve the voxel representation. This master presents an innovative combination of steps leading to the creation of a 3D model from a set of existing images or from a series of images capture one after another leading to a real-time creation of a 3D model.
Bertrand, Yan. "Implantation d’un CT sur rails en radio-oncologie au nouveau CHUM." Thèse, 2018. http://hdl.handle.net/1866/22189.
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