Sparse-View Cone Beam CT Reconstruction Using Data-Consistent Supervised and Adversarial Learning From Scarce Training Data-Reference-Cited by-同舟云学术

Sparse-View Cone Beam CT Reconstruction Using Data-Consistent Supervised and Adversarial Learning From Scarce Training Data

Published:2023 Issue: Volume:9 Page:13-28
ISSN:2333-9403
Container-title:IEEE Transactions on Computational Imaging
language:
Short-container-title:IEEE Trans. Comput. Imaging

Author:

Lahiri Anish¹^ORCID,Maliakal Gabriel²^ORCID,Klasky Marc L.³,Fessler Jeffrey A.¹^ORCID,Ravishankar Saiprasad⁴^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, USA

2. Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, MI, USA

3. Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA

4. Department of Computational Mathematics, Science and Engineering, and the Department of Biomedical Engineering, Michigan State University, East Lansing, MI, USA

Funder

National Nuclear Security Administration

Los Alamos National Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Mathematics,Computer Science Applications,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6745852/10038323/10008080.pdf?arnumber=10008080

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