Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Gregory Ongie"'
Publikováno v:
7th International Conference on Image Formation in X-Ray Computed Tomography.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c694659da8764a6671697d544a287120
https://doi.org/10.1117/12.2647039
https://doi.org/10.1117/12.2647039
Publikováno v:
IEEE Transactions on Computational Imaging. 7:661-674
Deep neural networks have been applied successfully to a wide variety of inverse problems arising in computational imaging. These networks are typically trained using a forward model that describes the measurement process to be inverted, which is oft
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::afa8fba1878328658678e0ee424ce24d
https://doi.org/10.1109/tci.2021.3094714
https://doi.org/10.1109/tci.2021.3094714
Publikováno v:
Medical Imaging 2022: Image Perception, Observer Performance, and Technology Assessment.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::98b07e31aee2196888a987c2cfefe279
https://doi.org/10.1117/12.2613050
https://doi.org/10.1117/12.2613050
Recent efforts on solving inverse problems in imaging via deep neural networks use architectures inspired by a fixed number of iterations of an optimization method. The number of iterations is typically quite small due to difficulties in training net
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10e75b0f06b9b3e166c190359d7a6ecb
Autor:
Gregory Ongie, Rebecca Willett, Alexandros G. Dimakis, Richard G. Baraniuk, Christopher A. Metzler, Ajil Jalal
Recent work in machine learning shows that deep neural networks can be used to solve a wide variety of inverse problems arising in computational imaging. We explore the central prevailing themes of this emerging area and present a taxonomy that can b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b6f834ade575b0aaf7d707794e5dc56
http://arxiv.org/abs/2005.06001
http://arxiv.org/abs/2005.06001
Publikováno v:
Medical Imaging: Image Perception, Observer Performance, and Technology Assessment
Given the wide variety of CT reconstruction algorithms currently available { from filtered back projection, to non- linear iterative algorithms, and now even deep learning approaches { there is a pressing need for reconstruction quality metrics that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::75fb1ab62569feded1302ffb504ea540
https://doi.org/10.1117/12.2549817
https://doi.org/10.1117/12.2549817
Publikováno v:
IEEE Transactions on Medical Imaging. 34:2417-2428
We introduce a fast iterative shrinkage algorithm for patch-smoothness regularization of inverse problems in medical imaging. This approach is enabled by the reformulation of current non-local regularization schemes as an alternating algorithm to min
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8acb22efbaa8eee34a22deeb75881130
https://doi.org/10.1109/tmi.2015.2398466
https://doi.org/10.1109/tmi.2015.2398466
Publikováno v:
Allerton
Low rank matrix completion (LRMC) has received tremendous attention in recent years. The low rank assumption means that the columns (or rows) of the matrix to be completed are points on a low-dimensional linear variety. This paper extends this thinki
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::570833ba08d1ac952423767c9fb8ce6d
https://doi.org/10.1109/allerton.2017.8262820
https://doi.org/10.1109/allerton.2017.8262820
Autor:
Dimitri Van De Ville, Yue Lu, Arvind Balachandrasekaran, Gregory Ongie, Manos Papadakis, Mathews Jacob, Sampurna Biswas
Publikováno v:
Wavelets and Sparsity XVII.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::00484c0bb1d70aaac4ba6fd8776d3b47
https://doi.org/10.1117/12.2275352
https://doi.org/10.1117/12.2275352
Publikováno v:
EMBC
We introduce a fast iterative non-local shrinkage algorithm to recover MRI data from undersampled Fourier measurements. This approach is enabled by the reformulation of current non-local schemes as an alternating algorithm to minimize a global criter
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4fb40462f234eb95f4a45fc4653edd5f