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Self-supervised learning for CT image denoising and reconstruction: a review.

Authors :
Choi, Kihwan
Source :
Biomedical Engineering Letters; Nov2024, Vol. 14 Issue 6, p1207-1220, 14p
Publication Year :
2024

Abstract

This article reviews the self-supervised learning methods for CT image denoising and reconstruction. Currently, deep learning has become a dominant tool in medical imaging as well as computer vision. In particular, self-supervised learning approaches have attracted great attention as a technique for learning CT images without clean/noisy references. After briefly reviewing the fundamentals of CT image denoising and reconstruction, we examine the progress of deep learning in CT image denoising and reconstruction. Finally, we focus on the theoretical and methodological evolution of self-supervised learning for image denoising and reconstruction. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20939868
Volume :
14
Issue :
6
Database :
Complementary Index
Journal :
Biomedical Engineering Letters
Publication Type :
Academic Journal
Accession number :
180500473
Full Text :
https://doi.org/10.1007/s13534-024-00424-w