The Experts below are selected from a list of 870 Experts worldwide ranked by ideXlab platform
J. Webster Stayman - One of the best experts on this subject based on the ideXlab platform.
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High-Fidelity Modeling of Shift-Variant Focal-Spot Blur for High-Resolution CT
arXiv: Medical Physics, 2017Co-Authors: Steven Tilley, Wojciech Zbijewski, J. Webster StaymanAbstract:Dedicated application-specific CT systems are popular solutions to high-resolution clinical needs. Some applications, such as mammography and extremities imaging, require spatial resolution beyond current capabilities. Thorough understanding of system properties may help tailor system design, acquisition protocols, and reconstruction algorithms to improve image quality. Using a high-fidelity measurement Model, we analyze the effects of shift-variant focal spot Blur due to depth-dependence and anode angulation on image quality throughout the three-dimensional field of view of a simulated extremities scanner. A Model of the shift-variant Blur associated with this device is then incorporated into a Model-Based Iterative Reconstruction (MBIR) algorithm, which is then compared to FDK and MBIR with simpler Blur Models at select locations throughout the field of view. We show that shift-variant focal spot Blur leads to location-dependent imaging performance. Furthermore, changing the orientation of the X-ray tube alters this spatial dependence. The analysis suggests methods to improve imaging performance based on specific image quality needs. The results also demonstrate that image quality can be improved by combining accurate Blur Modeling with MBIR. Specifically, across the entire field of view, MBIR with shift-variant Blur Modeling yielded the best image quality, followed by MBIR with a shift-invariant Blur Model, MBIR with an identity Blur Model, and FDK, respectively. These results suggest a number of opportunities for the optimization of imaging system performance in the hardware setup, the imaging protocol, and the reconstruction approach. While the high-fidelity Models used here are applied using the specifications of a dedicated extremities imaging system, the methods are general and may be applied to optimize imaging performance in any CT system.
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Modeling shift-variant X-ray focal spot Blur for high-resolution flat-panel cone-beam CT
arXiv: Medical Physics, 2016Co-Authors: Steven Tilley, Wojciech Zbijewski, Jeffrey H. Siewerdsen, J. Webster StaymanAbstract:Flat-panel cone-beam CT (CBCT) has been applied clinically in a number of high-resolution applications. Increasing geometric magnification can potentially improve resolution, but also increases Blur due to an extended x-ray focal-spot. We present a shift-variant focal-spot Blur Model and incorporate it into a Model-based iterative-reconstruction algorithm. We apply this algorithm to simulation and CBCT test-bench data. In a trabecular bone simulation study, we find traditional reconstruction approaches without a Blur Model exhibit shift-variant resolution properties that depend greatly on the acquisition protocol (e.g. short vs. full scans) and the anode angles of the rays used to reconstruct a particular region. For physical CBCT experiments focal spot Blur was characterized and a spatial resolution phantom was scanned and reconstructed. In both experiments image quality using the shift-variant Model was significantly improved over approaches that Modeled no Blur or only a shift-invariant Blur, suggesting a potential means to overcome traditional CBCT spatial resolution and system design limitations.
Andrew I. Comport - One of the best experts on this subject based on the ideXlab platform.
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A unified rolling shutter and motion Blur Model for 3d visual registration
2013Co-Authors: Maxime Meilland, Tom Drummond, Andrew I. ComportAbstract:Motion Blur and rolling shutter deformations both inhibit visual motion registration, whether it be due to a moving sensor or a moving target. Whilst both deformations exist simultaneously, no Models have been proposed to handle them together. Furthermore, neither deformation has been considered previously in the context of monocular fullimage 6 degrees of freedom registration or RGB-D structure and motion. As will be shown, rolling shutter deformation is observed when a camera moves faster than a single pixel in parallax between subsequent scan-lines. Blur is a function of the pixel exposure time and the motion vector. In this paper a complete dense 3D registration Model will be derived to account for both motion Blur and rolling shutter deformations simultaneously. Various approaches will be compared with respect to ground truth and live real-time performance will be demonstrated for complex scenarios where both Blur and shutter deformations are dominant.
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ICCV - A Unified Rolling Shutter and Motion Blur Model for 3D Visual Registration
2013 IEEE International Conference on Computer Vision, 2013Co-Authors: Maxime Meilland, Tom Drummond, Andrew I. ComportAbstract:Motion Blur and rolling shutter deformations both inhibit visual motion registration, whether it be due to a moving sensor or a moving target. Whilst both deformations exist simultaneously, no Models have been proposed to handle them together. Furthermore, neither deformation has been considered previously in the context of monocular full-image 6 degrees of freedom registration or RGB-D structure and motion. As will be shown, rolling shutter deformation is observed when a camera moves faster than a single pixel in parallax between subsequent scan-lines. Blur is a function of the pixel exposure time and the motion vector. In this paper a complete dense 3D registration Model will be derived to account for both motion Blur and rolling shutter deformations simultaneously. Various approaches will be compared with respect to ground truth and live real-time performance will be demonstrated for complex scenarios where both Blur and shutter deformations are dominant.
Steven Tilley - One of the best experts on this subject based on the ideXlab platform.
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High-Fidelity Modeling of Shift-Variant Focal-Spot Blur for High-Resolution CT
arXiv: Medical Physics, 2017Co-Authors: Steven Tilley, Wojciech Zbijewski, J. Webster StaymanAbstract:Dedicated application-specific CT systems are popular solutions to high-resolution clinical needs. Some applications, such as mammography and extremities imaging, require spatial resolution beyond current capabilities. Thorough understanding of system properties may help tailor system design, acquisition protocols, and reconstruction algorithms to improve image quality. Using a high-fidelity measurement Model, we analyze the effects of shift-variant focal spot Blur due to depth-dependence and anode angulation on image quality throughout the three-dimensional field of view of a simulated extremities scanner. A Model of the shift-variant Blur associated with this device is then incorporated into a Model-Based Iterative Reconstruction (MBIR) algorithm, which is then compared to FDK and MBIR with simpler Blur Models at select locations throughout the field of view. We show that shift-variant focal spot Blur leads to location-dependent imaging performance. Furthermore, changing the orientation of the X-ray tube alters this spatial dependence. The analysis suggests methods to improve imaging performance based on specific image quality needs. The results also demonstrate that image quality can be improved by combining accurate Blur Modeling with MBIR. Specifically, across the entire field of view, MBIR with shift-variant Blur Modeling yielded the best image quality, followed by MBIR with a shift-invariant Blur Model, MBIR with an identity Blur Model, and FDK, respectively. These results suggest a number of opportunities for the optimization of imaging system performance in the hardware setup, the imaging protocol, and the reconstruction approach. While the high-fidelity Models used here are applied using the specifications of a dedicated extremities imaging system, the methods are general and may be applied to optimize imaging performance in any CT system.
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Modeling shift-variant X-ray focal spot Blur for high-resolution flat-panel cone-beam CT
arXiv: Medical Physics, 2016Co-Authors: Steven Tilley, Wojciech Zbijewski, Jeffrey H. Siewerdsen, J. Webster StaymanAbstract:Flat-panel cone-beam CT (CBCT) has been applied clinically in a number of high-resolution applications. Increasing geometric magnification can potentially improve resolution, but also increases Blur due to an extended x-ray focal-spot. We present a shift-variant focal-spot Blur Model and incorporate it into a Model-based iterative-reconstruction algorithm. We apply this algorithm to simulation and CBCT test-bench data. In a trabecular bone simulation study, we find traditional reconstruction approaches without a Blur Model exhibit shift-variant resolution properties that depend greatly on the acquisition protocol (e.g. short vs. full scans) and the anode angles of the rays used to reconstruct a particular region. For physical CBCT experiments focal spot Blur was characterized and a spatial resolution phantom was scanned and reconstructed. In both experiments image quality using the shift-variant Model was significantly improved over approaches that Modeled no Blur or only a shift-invariant Blur, suggesting a potential means to overcome traditional CBCT spatial resolution and system design limitations.
Yu-wing Tai - One of the best experts on this subject based on the ideXlab platform.
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Registration Based Non-uniform Motion DeBlurring
Computer Graphics Forum, 2012Co-Authors: Sunghyun Cho, Yu-wing Tai, Cho Hojin, Seungyong LeeAbstract:This paper proposes an algorithm which uses image registration to estimate a non-uniform motion Blur point spread function (PSF) caused by camera shake. Our study is based on a motion Blur Model which Models Blur effects of camera shakes using a set of planar perspective projections (i.e., homographies). This representation can fully describe motions of camera shakes in 3D which cause non-uniform motion Blurs. We transform the non-uniform PSF estimation problem into a set of image registration problems which estimate homographies of the motion Blur Model one-by-one through the Lucas-Kanade algorithm. We demonstrate the performance of our algorithm using both synthetic and real world examples. We also discuss the effectiveness and limitations of our algorithm for non-uniform deBlurring. © 2012 Wiley Periodicals, Inc.
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Richardson-Lucy DeBlurring for Scenes under a Projective Motion Path
IEEE transactions on pattern analysis and machine intelligence, 2010Co-Authors: Yu-wing Tai, Ping Tan, Michael S. BrownAbstract:This paper addresses how to Model and correct image Blur that arises when a camera undergoes ego motion while observing a distant scene. In particular, we discuss how the Blurred image can be Modeled as an integration of the clear scene under a sequence of planar projective transformations (i.e., homographies) that describe the camera's path. This projective motion path Blur Model is more effective at Modeling the spatially varying motion Blur exhibited by ego motion than conventional methods based on space-invariant Blur kernels. To correct the Blurred image, we describe how to modify the Richardson-Lucy (RL) algorithm to incorporate this new Blur Model. In addition, we show that our projective motion RL algorithm can incorporate state-of-the-art regularization priors to improve the deBlurred results. The projective motion path Blur Model, along with the modified RL algorithm, is detailed, together with experimental results demonstrating its overall effectiveness. Statistical analysis on the algorithm's convergence properties and robustness to noise is also provided.
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CVPR - Coded exposure imaging for projective motion deBlurring
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010Co-Authors: Yu-wing Tai, Naejin Kong, Stephen Lin, Sung Yong ShinAbstract:We propose a method for deBlurring of spatially variant object motion. A principal challenge of this problem is how to estimate the point spread function (PSF) of the spatially variant Blur. Based on the projective motion Blur Model of [27], we present a Blur estimation technique that jointly utilizes a coded exposure camera and simple user interactions to recover the PSF. With this spatially variant PSF, objects that exhibit projective motion can be effectively de-Blurred. We validate this method with several challenging image examples.
Maxime Meilland - One of the best experts on this subject based on the ideXlab platform.
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A unified rolling shutter and motion Blur Model for 3d visual registration
2013Co-Authors: Maxime Meilland, Tom Drummond, Andrew I. ComportAbstract:Motion Blur and rolling shutter deformations both inhibit visual motion registration, whether it be due to a moving sensor or a moving target. Whilst both deformations exist simultaneously, no Models have been proposed to handle them together. Furthermore, neither deformation has been considered previously in the context of monocular fullimage 6 degrees of freedom registration or RGB-D structure and motion. As will be shown, rolling shutter deformation is observed when a camera moves faster than a single pixel in parallax between subsequent scan-lines. Blur is a function of the pixel exposure time and the motion vector. In this paper a complete dense 3D registration Model will be derived to account for both motion Blur and rolling shutter deformations simultaneously. Various approaches will be compared with respect to ground truth and live real-time performance will be demonstrated for complex scenarios where both Blur and shutter deformations are dominant.
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ICCV - A Unified Rolling Shutter and Motion Blur Model for 3D Visual Registration
2013 IEEE International Conference on Computer Vision, 2013Co-Authors: Maxime Meilland, Tom Drummond, Andrew I. ComportAbstract:Motion Blur and rolling shutter deformations both inhibit visual motion registration, whether it be due to a moving sensor or a moving target. Whilst both deformations exist simultaneously, no Models have been proposed to handle them together. Furthermore, neither deformation has been considered previously in the context of monocular full-image 6 degrees of freedom registration or RGB-D structure and motion. As will be shown, rolling shutter deformation is observed when a camera moves faster than a single pixel in parallax between subsequent scan-lines. Blur is a function of the pixel exposure time and the motion vector. In this paper a complete dense 3D registration Model will be derived to account for both motion Blur and rolling shutter deformations simultaneously. Various approaches will be compared with respect to ground truth and live real-time performance will be demonstrated for complex scenarios where both Blur and shutter deformations are dominant.