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Super-Iterative Image Reconstruction in PET
IEEE Transactions on Computational Imaging, 2021Despite its success in many biomedical applications, Positron Emission Tomography (PET) has the drawback of typically having lower spatial resolution and higher noise respect to other medical imaging techniques. The best achievable spatial resolution in PET scanners is limited by factors such as the positron range, non-collinearity and the size of the ...
Pablo Galve +6 more
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2016
An improved iterative reconstruction method to reconstruct a first image includes generating an imaging beam, receiving said imaging beam on a detector array, generating projection data based on said imaging beams received by said detector array, providing said projection data to an image reconstructor, enlarging one of a plurality of voxels and a ...
De Man, Bruno Kristiaan Bernard +6 more
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An improved iterative reconstruction method to reconstruct a first image includes generating an imaging beam, receiving said imaging beam on a detector array, generating projection data based on said imaging beams received by said detector array, providing said projection data to an image reconstructor, enlarging one of a plurality of voxels and a ...
De Man, Bruno Kristiaan Bernard +6 more
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Adaptive iterative reconstruction
SPIE Proceedings, 2011It is well known that, in CT reconstruction, Maximum A Posteriori (MAP) reconstruction based on a Poisson noise model can be well approximated by Penalized Weighted Least Square (PWLS) minimization based on a data dependent Gaussian noise model. We study minimization of the PWLS objective function using the Gradient Descent (GD) method, and show that ...
H. Bruder +5 more
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Abnormal Detection by Iterative Reconstruction
2016We propose an automatic abnormal detection method using subspace and iterative reconstruction for visual inspection. In visual inspection, we obtain many normal images and little abnormal images. Thus, we use a subspace method which is trained from only normal images.
Kenta Toyoda, Kazuhiro Hotta
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European Radiology, 2014
The purpose of this study was to compare cranial CT (CCT) image quality (IQ) of the MBIR algorithm with standard iterative reconstruction (ASiR).In this institutional review board (IRB)-approved study, raw data sets of 100 unenhanced CCT examinations (120 kV, 50-260 mAs, 20 mm collimation, 0.984 pitch) were reconstructed with both ASiR and MBIR. Signal-
S, Notohamiprodjo +6 more
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The purpose of this study was to compare cranial CT (CCT) image quality (IQ) of the MBIR algorithm with standard iterative reconstruction (ASiR).In this institutional review board (IRB)-approved study, raw data sets of 100 unenhanced CCT examinations (120 kV, 50-260 mAs, 20 mm collimation, 0.984 pitch) were reconstructed with both ASiR and MBIR. Signal-
S, Notohamiprodjo +6 more
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Approximate 3D iterative reconstruction for SPECT
Medical Physics, 1997Compared with slice‐by‐slice approaches for SPECT reconstruction, three‐dimensional iterative methods provide a more accurate physical model and an improved SPECT image. Clinical application of these methods, however, is limited primarily by their computational demands.
D R, Gilland +3 more
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Convergence of iterative algorithms for image reconstruction
Proceedings IEEE International Symposium on Biomedical Imaging, 2003We introduce a general iterative scheme for image reconstruction based on Landweber's method. Within our configuration, the block-iterative (BI) version can be formulated from its simultaneous version easily, and vice versa. This provides the mechanism to formulate new algorithms from known algorithms.
Ming Jiang 0001, Ge Wang 0001
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Iterative Breast Tomosynthesis Image Reconstruction
SIAM Journal on Scientific Computing, 2013In digital tomosynthesis imaging, multiple projections of an object are obtained along a small range of different incident angles in order to reconstruct a pseudo-3D representation of the object. In this paper we discuss a mathematical model for polyenergetic digital breast tomosynthesis image reconstruction that explicitly takes into account various ...
Veronica Mejia Bustamante +3 more
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Learning Iterative Image Reconstruction
2003Successful image reconstruction requires the recognition of a scene and the generation of a clean image of that scene. In this chapter, I show how to use Neural Abstraction Pyramid networks for both analysis and synthesis of images. The networks have a hierarchical architecture which represents images in multiple scales with different degrees of ...
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Iterative relaxation methods for image reconstruction
Proceedings of the 1975 annual conference on - ACM 75, 1975The problem of recovering an image (a function of two variables) from experimentally available integrals of its grayness over thin strips is of great importance in a large number of scientific areas. An important version of the problem in medicine is that of obtaining the exact density distribution within the human body from X-ray projections.One ...
Gabor T. Herman +2 more
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