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Letteratura scientifica selezionata sul tema "Reconstruction à angles limités"

Autore: Grafiati

Pubblicato: 5 aprile 2025

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Articoli di riviste sul tema "Reconstruction à angles limités"

Schüle, T., C. Schnörr, J. Hornegger e S. Weber. "A Linear Programming Approach to Limited Angle 3D Reconstruction from DSA Projections". Methods of Information in Medicine 43, n. 04 (2004): 320–26. http://dx.doi.org/10.1055/s-0038-1633875.

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Summary Objectives: We investigate the feasibility of binary-valued 3D tomographic reconstruction using only a small number of projections acquired over a limited range of angles. Methods: Regularization of this strongly ill-posed problem is achieved by (i) confining the reconstruction to binary vessel/non-vessel decisions, and (ii) by minimizing a global functional involving a smoothness prior. Results: Our approach successfully reconstructs volumetric vessel structures from three projections taken within 90°. The percentage of reconstructed voxels differing from ground truth is below 1%. Conclusion: We demonstrate that for particular applications – like Digital Subtraction Angiography – 3D reconstructions are possible where conventional methods must fail, due to a severely limited imaging geometry. This could play an important role for dose reduction and 3D reconstruction using non-conventional technical setups.

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Shen, Enxiang, Yuxin Wang, Jie Yuan e Paul L. Carson. "Limited-Angle Computer Tomography with Truncated Projection Artifacts Removal". Applied Sciences 12, n. 22 (16 novembre 2022): 11627. http://dx.doi.org/10.3390/app122211627.

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Breast cancer is the most common cancer in women and the second most common cancer in the world. Digital breast tomosynthesis (DBT) is an effective medical imaging method. It can reduce the overlap of breast tissue in reconstructed images, which is beneficial to the early detection of breast cancer. DBT uses projection data from a limited range of angles and the simultaneous algebraic reconstruction technique (SART) based reconstruction method. Since the detector’s field of view (FOV) is limited, the updates of the large projection angles in SART cannot include all the voxels of the imaging target, which causes truncated projection artifacts (TPA) at the edges of the image. In this work, we use the images reconstructed by SART to perform re-projection on the virtually expanded detector panel and use a gradient calculation method to compensate for missing projection data to ensure that each update can include all the voxels. Experiments on simulation and human breast demonstrated that TPA can be effectively reduced while retaining the detailed tissue structure, thus improving the image quality at the border and recovering the obscured structural information. It might provide a better imaging result for the consequential clinical diagnosis.

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Krimmel, S., J. Baumann, Z. Kiss, A. Kuba, A. Nagy e J. Stephan. "Discrete tomography for reconstruction from limited view angles in non-destructive testing". Electronic Notes in Discrete Mathematics 20 (luglio 2005): 455–74. http://dx.doi.org/10.1016/j.endm.2005.05.078.

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Huang, Yixing, Shengxiang Wang, Yong Guan e Andreas Maier. "Limited angle tomography for transmission X-ray microscopy using deep learning". Journal of Synchrotron Radiation 27, n. 2 (13 febbraio 2020): 477–85. http://dx.doi.org/10.1107/s160057752000017x.

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In transmission X-ray microscopy (TXM) systems, the rotation of a scanned sample might be restricted to a limited angular range to avoid collision with other system parts or high attenuation at certain tilting angles. Image reconstruction from such limited angle data suffers from artifacts because of missing data. In this work, deep learning is applied to limited angle reconstruction in TXMs for the first time. With the challenge to obtain sufficient real data for training, training a deep neural network from synthetic data is investigated. In particular, U-Net, the state-of-the-art neural network in biomedical imaging, is trained from synthetic ellipsoid data and multi-category data to reduce artifacts in filtered back-projection (FBP) reconstruction images. The proposed method is evaluated on synthetic data and real scanned chlorella data in 100° limited angle tomography. For synthetic test data, U-Net significantly reduces the root-mean-square error (RMSE) from 2.55 × 10−3 µm−1 in the FBP reconstruction to 1.21 × 10−3 µm−1 in the U-Net reconstruction and also improves the structural similarity (SSIM) index from 0.625 to 0.920. With penalized weighted least-square denoising of measured projections, the RMSE and SSIM are further improved to 1.16 × 10−3 µm−1 and 0.932, respectively. For real test data, the proposed method remarkably improves the 3D visualization of the subcellular structures in the chlorella cell, which indicates its important value for nanoscale imaging in biology, nanoscience and materials science.

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Gong, Changcheng, Li Zeng, Yumeng Guo, Chengxiang Wang e Shengmiao Wang. "Multiple limited-angles computed tomography reconstruction based on multi-direction total variation minimization". Review of Scientific Instruments 89, n. 12 (dicembre 2018): 125121. http://dx.doi.org/10.1063/1.5030673.

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Goy, Alexandre, Girish Rughoobur, Shuai Li, Kwabena Arthur, Akintunde I. Akinwande e George Barbastathis. "High-resolution limited-angle phase tomography of dense layered objects using deep neural networks". Proceedings of the National Academy of Sciences 116, n. 40 (16 settembre 2019): 19848–56. http://dx.doi.org/10.1073/pnas.1821378116.

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We present a machine learning-based method for tomographic reconstruction of dense layered objects, with range of projection angles limited to ±10○. Whereas previous approaches to phase tomography generally require 2 steps, first to retrieve phase projections from intensity projections and then to perform tomographic reconstruction on the retrieved phase projections, in our work a physics-informed preprocessor followed by a deep neural network (DNN) conduct the 3-dimensional reconstruction directly from the intensity projections. We demonstrate this single-step method experimentally in the visible optical domain on a scaled-up integrated circuit phantom. We show that even under conditions of highly attenuated photon fluxes a DNN trained only on synthetic data can be used to successfully reconstruct physical samples disjoint from the synthetic training set. Thus, the need for producing a large number of physical examples for training is ameliorated. The method is generally applicable to tomography with electromagnetic or other types of radiation at all bands.

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Dang Nguyen, Ngoc An, Hoang Nhut Huynh, Trung Nghia Tran e Koichi Shimizu. "Reconstructing 3D De-Blurred Structures from Limited Angles of View through Turbid Media Using Deep Learning". Applied Sciences 14, n. 5 (20 febbraio 2024): 1689. http://dx.doi.org/10.3390/app14051689.

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Recent studies in transillumination imaging for developing an optical computed tomography device for small animal and human body parts have used deep learning networks to suppress the scattering effect, estimate depth information of light-absorbing structures, and reconstruct three-dimensional images of de-blurred structures. However, they still have limitations, such as knowing the information of the structure in advance, only processing simple structures, limited effectiveness for structures with a depth of about 15 mm, and the need to use separated deep learning networks for de-blurring and estimating information. Furthermore, the current technique cannot handle multiple structures distributed at different depths next to each other in the same image. To overcome the mentioned limitations in transillumination imaging, this study proposed a pixel-by-pixel scanning technique in combination with deep learning networks (Attention Res-UNet for scattering suppression and DenseNet-169 for depth estimation) to estimate the existence of each pixel and the relative structural depth information. The efficacy of the proposed method was evaluated through experiments that involved a complex model within a tissue-equivalent phantom and a mouse, achieving a reconstruction error of 2.18% compared to the dimensions of the ground truth when using the fully convolutional network. Furthermore, we could use the depth matrix obtained from the convolutional neural network (DenseNet-169) to reconstruct the absorbing structures using a binary thresholding method, which produced a reconstruction error of 6.82%. Therefore, only one convolutional neural network (DenseNet-169) must be used for depth estimation and explicit image reconstruction. Therefore, it reduces time and computational resources. With depth information at each pixel, reconstruction of 3D image of the de-blurred structures could be performed even from a single blurred image. These results confirm the feasibility and robustness of the proposed pixel-by-pixel scanning technique to restore the internal structure of the body, including intricate networks such as blood vessels or abnormal tissues.

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Ohler, M., M. Sanchez del Rio, A. Tuffanelli, M. Gambaccini, A. Taibi, A. Fantini e G. Pareschi. "X-ray topographic determination of the granular structure in a graphite mosaic crystal: a three-dimensional reconstruction". Journal of Applied Crystallography 33, n. 4 (1 agosto 2000): 1023–30. http://dx.doi.org/10.1107/s0021889800005975.

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Section topographs recorded at different spatial locations and at different rocking angles of a highly oriented pyrolytic graphite (HOPG) crystal allow three-dimensional maps of the local angular-dependent scattering power to be obtained. This is performed with a direct reconstruction from the intensity distribution on such topographs. The maps allow the extraction of information on local structural parameters such as size, form and internal mosaic spread of crystalline domains. This data analysis leads to a new method for the characterization of mosaic crystals. Perspectives and limits of applicability of this method are discussed.

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Van Veen, Dave, Jesús G. Galaz-Montoya, Liyue Shen, Philip Baldwin, Akshay S. Chaudhari, Dmitry Lyumkis, Michael F. Schmid, Wah Chiu e John Pauly. "Missing Wedge Completion via Unsupervised Learning with Coordinate Networks". International Journal of Molecular Sciences 25, n. 10 (17 maggio 2024): 5473. http://dx.doi.org/10.3390/ijms25105473.

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Cryogenic electron tomography (cryoET) is a powerful tool in structural biology, enabling detailed 3D imaging of biological specimens at a resolution of nanometers. Despite its potential, cryoET faces challenges such as the missing wedge problem, which limits reconstruction quality due to incomplete data collection angles. Recently, supervised deep learning methods leveraging convolutional neural networks (CNNs) have considerably addressed this issue; however, their pretraining requirements render them susceptible to inaccuracies and artifacts, particularly when representative training data is scarce. To overcome these limitations, we introduce a proof-of-concept unsupervised learning approach using coordinate networks (CNs) that optimizes network weights directly against input projections. This eliminates the need for pretraining, reducing reconstruction runtime by 3–20× compared to supervised methods. Our in silico results show improved shape completion and reduction of missing wedge artifacts, assessed through several voxel-based image quality metrics in real space and a novel directional Fourier Shell Correlation (FSC) metric. Our study illuminates benefits and considerations of both supervised and unsupervised approaches, guiding the development of improved reconstruction strategies.

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Hui, CheukKai, Daniel Robertson e Sam Beddar. "3D reconstruction of scintillation light emission from proton pencil beams using limited viewing angles—a simulation study". Physics in Medicine and Biology 59, n. 16 (23 luglio 2014): 4477–92. http://dx.doi.org/10.1088/0031-9155/59/16/4477.

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Più fonti

Tesi sul tema "Reconstruction à angles limités"

Laurendeau, Matthieu. "Tomographic incompleteness maps and application to image reconstruction and stationary scanner design". Electronic Thesis or Diss., Lyon, INSA, 2024. http://www.theses.fr/2024ISAL0130.

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La tomographie par rayons X est l'une des modalités d'imagerie les plus couramment utilisées dans les domaines médical et industriel. Ces dernières années, de nouvelles sources à rayons X ont été développées sur la base de cathodes en nanotubes de carbone (CNT). Leur taille compacte permet de concevoir une nouvelle génération de scanner multi-sources. Contrairement aux systèmes traditionels dotés d'une seule source mobile, ces scanners adoptent des architectures stationnaires où plusieurs sources sont fixées à des positions précises. Cela profiterait à la fois à l'industrie, avec des scanners moins chers, et aux applications médicales, avec des scanners légers et mobiles qui pourraient être déployés directement sur les sites d'urgence. Cependant, ce type de scanner a une couverture angulaire limitée, posant des défis importants en reconstruction d'images. Cette thèse se concentre sur la conception de tels scanners stationnaires. Trois axes d'étude sont examinés. La première contribution est le développement d'une métrique indépendante de l'objet, afin d'évaluer la capacité de reconstruction d'une géométrie de scanner. Basée sur la condition de Tuy, la métrique évalue l'incomplétude tomographique locale et est visualisée selon des cartes de champs vectoriels 3D. Elle est ensuite améliorée pour traiter les projections tronquées, la rendant plus applicable aux configurations du monde réel. Ces cartes permettent de classer différentes géométries, de prédire la qualité de reconstruction et d'identifier l'origine des artefacts géométriques. Elle est calculée pour une variété de géométries, y compris des scanners existants. La seconde est une nouvelle méthode de régularisation locale qui permet de relever les défis de la reconstruction à angle limité. Basée sur une régularisation de type variation totale directionnelle (DTV), la méthode adapte la force et les poids directionnels à chaque voxel sélectionné à partir de la métrique introduite précédemment. Deux approches sont explorées : des poids directionnels basés sur le ratio par rapport aux axes de l'image ou basés sur l'ellipse. L'algorithme de reconstruction est évalué dans des simulations 2D et 3D, en considérant des données bruitées et non bruitées, ainsi que des données réelles. La troisième est un outil d'optimisation de la géométrie des scanners. Étant donné un nombre fixe de sources et une surface disponible pour leur positionnement, l'outil optimise l'emplacement des sources en minimisant l'incomplétude tomograhique de la région imagée. Plusieurs algorithmes d'optimisation sont implémentés et testés sur des scénarios simples 2D et 3D
Computed tomography (CT) is one of the most commonly used modality for three-dimensional (3D) imaging in the medical and industrial fields. In the past few years, new X-ray sources have been developed based on carbon nanotube (CNT) cathodes. Their compact size enables the design of a new generation of multi-source CT scanners. In contrast to traditional systems with a single moving source, these scanners often adopt stationary architectures where multiple sources are static. It would benefit both industry with cheaper and motionless systems and medical applications with light-weight and mobile scanners which could be brought to emergency sites. However, this type of scanner uses a fewer number of measurements, known as projections, and may acquire data with a limited range of angles, leading to well-known image reconstruction challenges. This thesis focuses on the design of such stationary CT scanners. Three axes of study were investigated. The first contribution is the development of an object-independent metric to assess the reconstruction capability of a given scanning geometry. Based on Tuy's condition, the metric evaluates local tomographic incompleteness and is visualized through 3D vector field maps. It is further extended to handle truncated projections, improving its applicability to real-world configurations. The metric enables ranking different geometries, predicting image quality reconstruction, and identifying the origin of geometric artifacts. It is applied to a variety of geometries, including existing scanners. The second is a novel local regularization method to address limited-angle reconstruction challenges. The method employs a directional total variation (DTV) regularizer whose strength and directional weights are adaptively selected at each voxel. The weights are determined based on the previously introduced metric. Two approaches for directional weights were explored: ratio-based weighting relative to image axes and ellipse-based weighting. The reconstruction algorithm is evaluated in both 2D and 3D simulations, considering noiseless and noisy data, as well as real data. The third is a tool for optimizing the geometry of CT scanners. Given a fixed number of sources and the surface area available for their positions, the tool optimizes the placement of sources based on the proposed metric. Several state-of-the-art optimization algorithms were implemented and tested on simple 2D and 3D scenarios

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Garnero, Line. "Reconstruction d'images tomographiques à partir d'un ensemble limite de projections". Paris 11, 1987. http://www.theses.fr/1987PA112012.

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Nous proposons dans cette thèse deux méthodes de reconstitution d'images tomographiques à partir d'un nombre limité de projections couvrant un angle de vue limité. Ces circonstances se rencontrent aussi bien en Imagerie Médicale, que dans d'autres domaines comme la microscopie électronique. Ces méthodes utilisent des informations a priori sur l'objet afin de retrouver les données manquantes. Nous avons appliqué une de ces méthodes aussi bien à reconstructions bidimensionnelles, que directement tridimensionnelles, et nous l'avons aussi utilisée dans deux cas concrets relevant du domaine des contrôles non destructifs et de la microimagerie plasma laser. Nous présentons aussi une étude des artéfacts paraissant sur les images tomographiques de Médecine Nucléaire à la suite de mauvaises conditions d'acquisition.

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Thompson, William. "Source firing patterns and reconstruction algorithms for a switched source, offset detector CT machine". Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/source-firing-patterns-and-reconstruction-algorithms-for-a-switched-source-offset-detector-ct-machine(97dc0705-45e2-4b7a-9ef3-1c8a58d5411a).html.

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We present a new theoretical model and reconstruction results for a new class of fast x-ray CT machine -- the Real Time Tomography (RTT) system, which uses switched sources and an offset detector array. We begin by reviewing elementary properties of the Radon and X-ray transforms, and limited angle tomography. Through the introduction of a new continuum model, that of sources covering the surface of a cylinder in R³, we show that the problem of three-dimensional reconstruction from RTT data reduces to inversion of the three-dimensional Radon transform with limited angle data. Using the Paley-Wiener theorem, we then prove the existence of a unique solution and give comments on stability and singularity detection. We show, first in the two-dimensional case, that the conjugate gradient least squares algorithm is suitable for CT reconstruction. By exploiting symmetries in the system, we then derive a method of applying CGLS to the three-dimensional inversion problem using stored matrix coefficients. The new concept of source firing order is introduced and formalised, and some novel visualisations are used to show how this affects aspects of the geometry of the system. We then perform a detailed numerical analysis using the condition number and SVD of the forward projection matrix $A$, to show that the choice of firing order affects the conditioning of the problem. Finally, we give reconstruction results from both simulated phantoms and real experimental data that support the numerical analysis.

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Servieres, Myriam. "Reconstruction Tomographique Mojette". Phd thesis, Université de Nantes, 2005. http://tel.archives-ouvertes.fr/tel-00426920.

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Une des thématiques abordée par l'équipe Image et Vidéo-Communication est la reconstruction tomographique discréte à l'aide de la transformée Mojette. Ma thèse s'inscrit dans le cadre de la reconstruction tomographique médicale. La transformée Mojette est une version discrète exacte de la transformée de Radon qui est l'outil mathématique permettant la reconstruction tomographique. Pour évaluer la qualité des reconstructions, nous avons utilisé des fantômes numériques 2D simples (objet carré, rond) en absence puis en présence de bruit. Le coeur de mon travail de thèse est la reconstruction d'un objet à l'aide d'un algorithme de rétroprojection filtrée exacte Mojette en absence de bruit s'appuyant sur la géométrie discrète. Pour un nombre fini de projections dépendant de la taille de l'objet à reconstruire la reconstruction est exacte. La majorité des tomographes industriels utilisent l'algorithme de rétroprojection de projections filtrées (Filtered Back Projection ou FBP) pour reconstruire la région d'intérêt. Cet algorithme possède deux défauts théoriques, un au niveau du filtre utilisé, l'autre au niveau de la rétroprojection elle-même. Nous avons pu mettre au point un algorithme de Mojette FBP. Cet algorithme fait partie des méthodes directes de reconstruction. Il a aussi été testé avec succès en présence de bruit. Cet algorithme permet une équivalence continu-discret lors de la reconstruction. L'étape de projection/rétroprojection Mojette présente la particularité intéressante de pouvoir être décrit par une matrice Toeplitz bloc Toeplitz. Pour utiliser cette propriété nous avons mis en oeuvre un algorithme de gradient conjugué.

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Barquero, Harold. "Limited angular range X-ray micro-computerized tomography : derivation of anatomical information as a prior for optical luminescence tomography". Thesis, Strasbourg, 2015. http://www.theses.fr/2015STRAE033/document.

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Cette thèse traite du couplage d'un tomographe optique par luminescence (LCT) et d'un tomographe par rayons X (XCT), en présence d'une contrainte sur la géométrie d'acquisition du XCT. La couverture angulaire du XCT est limitée à 90 degrés pour satisfaire des contraintes spatiales imposées par le LCT existant dans lequel le XCT doit être intégré. L'objectif est de dériver une information anatomique, à partir de l'image morphologique issue du XCT. Notre approche a consisté i) en l'implémentation d'un algorithme itératif régularisé pour la reconstruction tomographique à angle limité, ii) en la construction d'un atlas anatomique statistique de la souris et iii) en l'implémentation d'une chaîne automatique réalisant la segmentation des images XCT, l'attribution d'une signification anatomique aux éléments segmentés, le recalage de l'atlas statistique sur ces éléments et ainsi l'estimation des contours de certains tissus à faible contraste non identifiables en pratique dans une image XCT standard
This thesis addresses the combination of an Optical Luminescence Tomograph (OLT) and X-ray Computerized Tomograph (XCT), dealing with geometrical constraints defined by the existing OLT system in which the XCT must be integrated. The result is an acquisition geometry of XCT with a 90 degrees angular range only. The aim is to derive an anatomical information from the morphological image obtained with the XCT. Our approach consisted i) in the implementation of a regularized iterative algorithm for the tomographic reconstruction with limited angle data, ii) in the construction of a statistical anatomical atlas of the mouse and iii) in the implementation of an automatic segmentation workflow performing the segmentation of XCT images, the labelling of the segmented elements, the registration of the statistical atlas on these elements and consequently the estimation of the outlines of low contrast tissues that can not be identified in practice in a standard XCT image

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Frikel, Jürgen [Verfasser], Brigitte [Akademischer Betreuer] Forster-Heinlein, Samuli [Akademischer Betreuer] Siltanen e Rupert [Akademischer Betreuer] Lasser. "Reconstructions in limited angle x-ray tomography: Characterization of classical reconstructions and adapted curvelet sparse regularization / Jürgen Frikel. Gutachter: Brigitte Forster-Heinlein ; Samuli Siltanen ; Rupert Lasser. Betreuer: Brigitte Forster-Heinlein". München : Universitätsbibliothek der TU München, 2013. http://d-nb.info/1033164224/34.

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Banjak, Hussein. "X-ray computed tomography reconstruction on non-standard trajectories for robotized inspection". Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEI113/document.

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La tomographie par rayons X ou CT pour "Computed Tomography" est un outil puissant pour caractériser et localiser les défauts internes et pour vérifier la conformité géométrique d’un objet. Contrairement au cas des applications médicales, l’objet inspecté en Contrôle Non Destructif (CND) peut être très grand et composé de matériaux de haute atténuation, auquel cas l’utilisation d’une trajectoire circulaire pour l’inspection est impossible à cause de contraintes dans l’espace. Pour cette raison, l’utilisation de bras robotisés est l’une des nouvelles tendances reconnues dans la CT, car elle autorise plus de flexibilité dans la trajectoire d’acquisition et permet donc la reconstruction 3D de régions difficilement accessibles dont la reconstruction ne pourrait pas être assurée par des systèmes de tomographie industriels classiques. Une cellule de tomographie X robotisée a été installée au CEA. La plateforme se compose de deux bras robotiques pour positionner et déplacer la source et le détecteur en vis-à-vis. Parmi les nouveaux défis posés par la tomographie robotisée, nous nous concentrons ici plus particulièrement sur la limitation de l’ouverture angulaire imposée par la configuration en raison des contraintes importantes sur le mouvement mécanique de la plateforme. Le deuxième défi majeur est la troncation des projections qui se produit lorsque l’objet est trop grand par rapport au détecteur. L’objectif principal de ce travail consiste à adapter et à optimiser des méthodes de reconstruction CT pour des trajectoires non standard. Nous étudions à la fois des algorithmes de reconstruction analytiques et itératifs. Avant d’effectuer des inspections robotiques réelles, nous comptons sur des simulations numériques pour évaluer les performances des algorithmes de reconstruction sur des configurations d’acquisition de données. Pour ce faire, nous utilisons CIVA, qui est un outil de simulation pour le CND développé au CEA et qui est capable de simuler des données de projections réalistes correspondant à des configurations d’acquisition définies par l’utilisateur
X-ray computed tomography (CT) is a powerful tool to characterize or localize inner flaws and to verify the geometric conformity of an object. In contrast to medical applications, the scanned object in non-destructive testing (NDT) might be very large and composed of high-attenuation materials and consequently the use of a standard circular trajectory for data acquisition would be impossible due to constraints in space. For this reason, the use of robotic arms is one of the acknowledged new trends in NDT since it allows more flexibility in acquisition trajectories and therefore could be used for 3D reconstruction of hardly accessible regions that might be a major limitation of classical CT systems. A robotic X-ray inspection platform has been installed at CEA LIST. The considered system integrates two robots that move the X-ray generator and detector. Among the new challenges brought by robotic CT, we focus in this thesis more particularly on the limited access viewpoint imposed by the setup where important constraints control the mechanical motion of the platform. The second major challenge is the truncation of projections that occur when only a field-of-view (FOV) of the object is viewed by the detector. Before performing real robotic inspections, we highly rely on CT simulations to evaluate the capability of the reconstruction algorithm corresponding to a defined scanning trajectory and data acquisition configuration. For this purpose, we use CIVA which is an advanced NDT simulation platform developed at CEA and that can provide a realistic model for radiographic acquisitions and is capable of simulating the projection data corresponding to a specific CT scene defined by the user. Thus, the main objective of this thesis is to develop analytical and iterative reconstruction algorithms adapted to nonstandard trajectories and to integrate these algorithms in CIVA software as plugins of reconstruction

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"A hierarchical algorithm for limited-angle reconstruction". Massachusetts Institute of Technology, Laboratory for Information and Decision Systems], 1989. http://hdl.handle.net/1721.1/3110.

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Jerry L. Prince and Alan S. Willsky.
Caption title.
Includes bibliographical references.
Supported by the National Science Foundation. ECS-87-00903 Supported by the U.S. Army Research Office. DAAL03-86-K-0171

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Chang-Han, Tsai, e 蔡昌翰. "Image Reconstruction from Limited-Angle Data Sets". Thesis, 1999. http://ndltd.ncl.edu.tw/handle/72794854240341933866.

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碩士
國立海洋大學
電機工程學系
87
Reconstruction of cross-section images from the projections of an object is a widely used image processing technique. Traditional application of image reconstruction is the X-ray computed tomography for medical imaging, which reconstructs cross sections from projections of human body through the process of computing devices. In recent years, computed tomography has found its success in various applications, such as electron microscopy, astronomy, nondestructive evaluation, and many others. However, in many cases it is not possible to collect projection data over a complete angular range of. This is the so-called limited-angle problem that is mainly caused by the size of the object under test. Lack of complete angular coverge in CT scanning renders most of the Fourier-based image reconstruction methods, such as filtered back-projection (FBP), ineffective. As a result, they usually produce severe artifacts and also degrade accuracy in reconstructed cross sections. The iterative reconstruction-reprojection (IRR) algorithm proposed by Medoff et al. is commonly employed to solve the limited-angle problem. However, lack of sufficient prior information makes IRR less effective in the performance improvement of reconstructed images. Besides, the IRR algorithm has slow convergence rate in a recursive fashion to regularize the limited-angle problem. Therefore, how to maximize the use of prior and accelerate the convergence of the IRR algorithm is the main goal of the thesis. To improve the performance of the IRR algorithm, flawless prototype image is incorporated and difference constraint is developed as additional constraints of prior information. In addition, the constraint in frequency domain is also incorporated to increase convergence rate. Thus the performance of the IRR algorithm in effectiveness and efficiency can be greatly improved.

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"A projection space map method for limited angle reconstruction". Massachusetts Institute of Technology, Laboratory for Information and Decision Systems], 1987. http://hdl.handle.net/1721.1/3035.

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Jerry L. Prince and Alan S. Willsky.
Caption title.
Includes bibliographical references.
Supported by the National Science Foundation. ECS-8312921 Supported by the U.S. Army Research Office. DAAG29-84-K-005 DAAL03-86-K-1071 Partially supported by a U.S. Army Research Office Fellowship.

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Libri sul tema "Reconstruction à angles limités"

Reconstruction Algorithm Characterization and Performance Monitoring in Limited-Angle Chromotomography. Storming Media, 2003.

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Parker, Leroy. Workbook on Crime Scene Reconstruction of Shooting Incidents. AuthorHouse, 2005.

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Gunnell, Kristine Ashton, a cura di. Voices of American Women’s History from Reconstruction to the Present. Bloomsbury Publishing Inc, 2023. http://dx.doi.org/10.5040/9798216172505.

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This collection of historical and contemporary writing by women argues that, in addition to gender, identity markers such as race, class, religion, citizenship, sexuality, and marital status have influenced women’s lives in the United States for more than 200 years. Voices of American Women's History illustrates that gender alone has never defined women's experiences in America. Women from diverse backgrounds are represented in media and documents that include pamphlets, book excerpts, personal narratives, photographs, advertisements, congressional testimonies, and Supreme Court rulings. Such issues as abortion, marriage equality, domestic violence, and gender parity are shown from historical and contemporary angles, as this collection of primary sources allows readers and students to easily trace how women's lives and histories have and continue to intersect. With a historical context for each selection, the book also features structured activities to help teachers with class discussion and exams, including suggestions for further reading, document analysis, essay questions, and manageable research assignments.

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Konstam, Angus. Super-Battleships of World War I. Bloomsbury Publishing Plc, 2025. https://doi.org/10.5040/9781472866899.

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As World War I ended, the victors were developing a powerful new generation of 'hyper-dreadnoughts' and battlecruisers. Fully illustrated, this studies the big-gun warships that never were. 1918 was a moment of great naval change. Britain still had the largest fleet in the world, but its ships were ageing, and many of them were markedly inferior to the latest American and Japanese battleships. An arms race loomed between the war’s victors. In this book naval expert Angus Konstam studies and compares the battleships being designed between 1918 and 1922, which drew on the lessons of World War I. Britain was designing four G3-class 15in-gun battlecruisers, plus four N3 ‘hyper-dreadnoughts’ mounting colossal 18in guns. The US Navy was planning six new South Dakota battleships, carrying an incredible 12 16in guns, plus six Lexington-class battlecruisers. Japan was working on a similar project, and in 1920 the first of four Amagi-class battlecruisers were laid down. However, in 1922 this costly arms race was averted by the Washington Naval Treaty, which halted new battleship construction, and limited the major fleets. These battleships and battlecruisers were mostly cancelled and scrapped, with a few, such as Lexington and Akagi, converted into aircraft carriers. With new colour reconstructions of the G3, H3, South Dakota, Lexington and Amagi classes, this is the first book to study these never-built monster warships.

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Gustafson, Karl. Operator Geometry in Statistics. A cura di Frédéric Ferraty e Yves Romain. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.013.13.

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This article discusses the essentials of operator trigonometry developed by the author as it applies to statistics, with emphasis on key elements such as operator antieigenvalues, operator antieigenvectors, and operator turning angles. Operator trigonometry started out infinite dimensional, and remains infinite dimensional, even for Banach spaces. Thus, it is in principle applicable not only to infinite-dimensional statistics but also to cases involving functional data. The article first considers how operator trigonometry gives new geometrical meaning to statistical efficiency before formalizing it in a more deductive manner. It then explains the essentials of operator trigonometry and summarizes the ensuing developments. It also describes two lemmas that are implicit and essential to operator trigonometry, Antieigenvector Reconstruction Lemma and General Two-Component Lemma, and how operator trigonometry provides new geometry to statistics matrix inequalities and canonical correlations. Finally, it presents new results applying operator trigonometry to prediction theory and to association measures.

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Capitoli di libri sul tema "Reconstruction à angles limités"

Zhou, Bo, Xunyu Lin e Brendan Eck. "Limited Angle Tomography Reconstruction: Synthetic Reconstruction via Unsupervised Sinogram Adaptation". In Lecture Notes in Computer Science, 141–52. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20351-1_11.

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Fang, Lu. "Plenoptic Reconstruction". In Advances in Computer Vision and Pattern Recognition, 75–189. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-6915-5_4.

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AbstractEmpowered by advanced plenoptic sensing systems, light-field imaging becomes one of the most extensively used methods for capturing 3D views of a scene. In contrast to the traditional input to a 3D graphics system, namely, scenes consisting of pre-defined geometric primitives with different materials and sets of lights, the input to a light field is only a set of 2D images which are informative and cost effective. Unfortunately, due to the limited sensor resolution, existing systems must balance the spatial and angular resolution, i.e., one can obtain dense sampling images in the spatial dimension but only sparse sampling images in the angular (viewing angle) dimension or vice versa.

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Grünbaum, F. Alberto. "The Limited Angle Problem in Reconstruction from Projections". In Inverse Methods in Electromagnetic Imaging, 277–98. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-010-9444-3_18.

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Tam, K. C. "Limited-Angle Image Reconstruction in Non-Destructive Evaluation". In Signal Processing and Pattern Recognition in Nondestructive Evaluation of Materials, 205–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-83422-6_16.

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Mattarella, Bernardo Giorgio. "Sentenza 238/2014: EU Law and EU Values". In Remedies against Immunity?, 209–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-662-62304-6_10.

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AbstractThe relationship between Judgment 238/2014 of the Italian Constitutional Court and EU law is, at first glance, apparently weak, as the subject matter of the former is not governed by the latter, nor there have been any judgments from EU courts regarding the case. However, if one considers the origin and purpose of the EU itself and the state of relations between Italy and Germany, one cannot help but examine the case from a European law perspective. Judgment 238/2014 is relevant to European law in several ways, all of which concern not only military cooperation in the EU but also the protection of human rights, the risk of forum shopping and, above all, how reliable member states are in their mutual relations. European law in turn is relevant to the present case not so much because it offers solutions but because it shows a method for settling clashes between legal systems and illustrates its inherent difficulties. Sentenza 238/2014 is an unpersuasive judgment and can be criticized from different angles: the legal one (international and constitutional law), the factual reconstruction and the judgment’s likely effects. There are, however, two possibilities of resolving the situation that Sentenza has produced: firstly the legal one, which involves the use of all possible tools to limit its effects; and secondly the diplomatic one, which implies further negotiations. European law does not provide a ground for a preference between these two options, but it suggests that none of these ways is neglected.

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Huang, Yixing, Alexander Preuhs, Günter Lauritsch, Michael Manhart, Xiaolin Huang e Andreas Maier. "Data Consistent Artifact Reduction for Limited Angle Tomography with Deep Learning Prior". In Machine Learning for Medical Image Reconstruction, 101–12. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33843-5_10.

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Hanson, Kenneth M., e George W. Wecksung. "Bayesian Approach to Limited-Angle Reconstruction in Computed Tomography". In Maximum-Entropy and Bayesian Spectral Analysis and Estimation Problems, 255–72. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3961-5_15.

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Ben Yedder, Hanene, Majid Shokoufi, Ben Cardoen, Farid Golnaraghi e Ghassan Hamarneh. "Limited-Angle Diffuse Optical Tomography Image Reconstruction Using Deep Learning". In Lecture Notes in Computer Science, 66–74. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32239-7_8.

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Hammernik, Kerstin, Tobias Würfl, Thomas Pock e Andreas Maier. "A Deep Learning Architecture for Limited-Angle Computed Tomography Reconstruction". In Informatik aktuell, 92–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-54345-0_25.

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Yang, Guang, John H. Hipwell, Christine Tanner, David J. Hawkes e Simon R. Arridge. "Joint Registration and Limited-Angle Reconstruction of Digital Breast Tomosynthesis". In Breast Imaging, 713–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31271-7_92.

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Atti di convegni sul tema "Reconstruction à angles limités"

Nikishkov, Yuri, Ekaterina Bostaph e Andrew Makeev. "Nondestructive Inspection of Composite Structures based on Limited Angle X-ray Computed Tomography". In Vertical Flight Society 71st Annual Forum & Technology Display, 1–11. The Vertical Flight Society, 2015. http://dx.doi.org/10.4050/f-0071-2015-10262.

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New methods for nondestructive inspection and structural diagnostics of composites based on X-ray Computed Tomography led to improved evaluation of subsurface condition of composites. Currently, strict limitations related to generating X-ray projections all around the inspected object in a full CT scan prohibit CT application to large structures as the commercial industrial X-ray Computed Tomography systems utilize full 360-degree projection angle range for high-quality three-dimensional reconstruction of the inspected objects. The objective of this work is to assess the possibility for breaking through the current limits of X-ray Computed Tomography in order to enable high-fidelity nondestructive inspection of large aircraft structures. This work presents methods that use limited (less than 180-degree) number of angular projections for three-dimensional volume reconstruction. The limited-angle reconstructions are demonstrated on detection of the defects in composite articles pertinent to rotorcraft industry.

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Hori, K., e T. Hashimoto. "Direct image reconstruction using deep image prior in limited-angle SPECT". In 2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD), 1. IEEE, 2024. http://dx.doi.org/10.1109/nss/mic/rtsd57108.2024.10658412.

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Peng, Junbo, Richard Qiu, Tonghe Wang, Xiangyang Tang e Xiaofeng Yang. "Optimization-based image reconstruction for limited-angle dual-energy cone-beam CT". In Physics of Medical Imaging, a cura di John M. Sabol, Shiva Abbaszadeh e Ke Li, 83. SPIE, 2025. https://doi.org/10.1117/12.3047401.

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Gontarz, Michał, Wojciech Krauze, Vibekananda Dutta e Małgorzata Kujawińska. "Missing Cone Problem Correction with Deep Learning Based Segmentation". In Digital Holography and Three-Dimensional Imaging, M2A.4. Washington, D.C.: Optica Publishing Group, 2024. http://dx.doi.org/10.1364/dh.2024.m2a.4.

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The missing cone problem comes from limited angle scanning in Holographic Tomography. It causes an object elongation along the optical axis. This paper proposes creating a mask of the object via segmentation of reconstruction.

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Lv, L., F. Weng, G. Chen e Q. Huang. "A Deep Reconstruction Method for Limited-Angle and Low-Dose PET Imaging in Biology-Guided Radiotherapy". In 2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD), 1. IEEE, 2024. http://dx.doi.org/10.1109/nss/mic/rtsd57108.2024.10657296.

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"LIMITED ANGLE IMAGE RECONSTRUCTION USING FOUR HIGH RESOLUTION PROJECTION AXES AT CO-PRIME RATIO VIEW ANGLES". In International Conference on Computer Vision Theory and Applications. SciTePress - Science and and Technology Publications, 2008. http://dx.doi.org/10.5220/0001086300500057.

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Kolakalur, Anush, e Branislav Vuksanovic. "Iterative Reconstruction via Preserved Structures Approach for CT Images with Limited Scan Angles". In the 2019 International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3332340.3332354.

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Chan, Chi Kwan, Bingxin Huang, Tsz Fung Chan e Tsz Wai WONG. "Deep learning enables high-resolution reconstruction with limited detection angles in photoacoustic tomography". In Photons Plus Ultrasound: Imaging and Sensing 2024, a cura di Alexander A. Oraevsky e Lihong V. Wang. SPIE, 2024. http://dx.doi.org/10.1117/12.2692388.

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McDonald, Mark, e Mark A. Neifeld. "A technique for control of crosstalk noise in volume holography". In Holography. Washington, D.C.: Optica Publishing Group, 1996. http://dx.doi.org/10.1364/holography.1996.hmb.3.

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Volume holographic data storage offers many potential advantages over conventional magnetic mass storage including high parallelism, fast access, and high storage capacity. The high capacity of volume holography is partially attributable to the Bragg selectivity of thick media. For angularly multiplexed uniform gratings in media of finite thickness the Bragg diffraction efficiency has a well known sinc2(ϑ) dependence vs. dephasing (i.e., dephasing ϑ ∝ Δθ reconstruction angle for angular multiplexing). When a desired hologram is read out at a particular reconstruction angle, holograms stored at other angles will also be reconstructed, albeit with much lower efficiency. The superposition of the undesired reconstructions is known as crosstalk and this phenomenon has been investigated by several authors1,2. Such crosstalk will result in noise on the data detected from the desired hologram and can be diminished by reducing the density of the angular multiplexing2. Thus, crosstalk forms an upper bound on volume holographic memory density and capacity in the limit of small fixed noise sources. In this paper, we will consider the storage capacity limit imposed by crosstalk for a grating that is uniform throughout the finite medium and compare this with the limit obtained when the grating is apodized to reduce crosstalk. We will also show experimental verification of the apodization effect.

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Jin, Kyung-Chan, Sung-Ho Lee e Geon-Hee Kim. "Three-Dimensional Tomographic Reconstruction for Microscale Object Modeling". In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-51106.

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When scanning a relatively high resolution, thick object using conventional computed tomography (CT), the scanning axis of the X-ray gantry and detector is approximately perpendicular to the rotation axis of the sample. However, the inner interconnections in flat 3D devices are not reconstructed correctly in regular circular CT. In this paper, we focus on 3D tomographic reconstruction of inner interconnections by CT with particular attention to off-centered circular trajectory CT. However, in off-centered circular trajectory CT, the limited tilting angles of projections result in a missing wedge artifact because the object cannot usually be tilted beyond the limit and the data in the remaining projections are not obtained. Therefore, to alleviate missing wedge artifacts, we propose a reconstruction scheme of combining by filtered back projection (FBP) and constraint-based total variation minimization (c-TVM). In the c-TVM method, the artifact of missing wedge is minimized and the reconstructed region is suppressed with high frequency details while leaving the boundaries between homogeneous regions. In our experiments, the CT system obtained the projected images from a rotating sample using a fixed-mounted X-ray source and detector. We acquired 400 rotational projection images of a vertical connection in an off-centered circular trajectory with 30° tilting angles. We then reconstructed the aligned 3D views of the sample. Finally, we demonstrated that the proposed FBP and c-TVM combination with iterative processing yields a superior 3D reconstruction model to conventional tomography.

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Rapporti di organizzazioni sul tema "Reconstruction à angles limités"

Anirudh, R., H. Kim, K. Champley, J. J. Thiagarajan e A. Mohan. Improving Limited Angle CT Reconstruction with a Robust GAN Prior. Office of Scientific and Technical Information (OSTI), settembre 2019. http://dx.doi.org/10.2172/1598955.

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