Multilayer residual sparsifying transform (MARS) model for low‐dose CT image reconstruction

2021 ◽  
Author(s):  
Xikai Yang ◽  
Yong Long ◽  
Saiprasad Ravishankar
Keyword(s):  
Image Reconstruction ◽  
Low Dose ◽  
Ct Image ◽  
Low Dose Ct ◽  
Mars Model ◽  
Ct Image Reconstruction

scholarly journals Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction

2019 ◽  
Vol 1 (6) ◽  
pp. 269-276 ◽  
Author(s):  
Hongming Shan ◽  
Atul Padole ◽  
Fatemeh Homayounieh ◽  
Uwe Kruger ◽  
Ruhani Doda Khera ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Reconstruction ◽  
Deep Neural Network ◽  
Low Dose ◽  
Ct Image ◽  
Competitive Performance ◽  
Low Dose Ct ◽  
Ct Image Reconstruction

scholarly journals Low-Dose CT Image Reconstruction With a Deep Learning Prior

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 158647-158655
Author(s):  
Hyoung Suk Park ◽  
Kyungsang Kim ◽  
Kiwan Jeon
Keyword(s):  
Deep Learning ◽  
Image Reconstruction ◽  
Low Dose ◽  
Ct Image ◽  
Low Dose Ct ◽  
Ct Image Reconstruction

scholarly journals SPULTRA: Low-Dose CT Image Reconstruction With Joint Statistical and Learned Image Models

2020 ◽  
Vol 39 (3) ◽  
pp. 729-741 ◽  
Author(s):  
Siqi Ye ◽  
Saiprasad Ravishankar ◽  
Yong Long ◽  
Jeffrey A. Fessler
Keyword(s):  
Image Reconstruction ◽  
Low Dose ◽  
Ct Image ◽  
Low Dose Ct ◽  
Ct Image Reconstruction ◽  
Image Models

Clinical low dose CT image reconstruction using high-order total variation techniques

2010 ◽  
Author(s):  
Synho Do ◽  
W. Clem Karl ◽  
Mannudeep K. Kalra ◽  
Thomas J. Brady ◽  
Homer Pien
Keyword(s):  
Image Reconstruction ◽  
Total Variation ◽  
Low Dose ◽  
High Order ◽  
Ct Image ◽  
Low Dose Ct ◽  
Ct Image Reconstruction ◽  
Variation Techniques
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