Open AccessCT reconstruction algorithm based on truncated TV
Author(s) -
Hongbo Shi,
Aidi Wu,
Shidi Yang,
Dongjiang Ji
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1920/1/012036
Subject(s) - smoothness , algorithm , algebraic number , computer science , image (mathematics) , artificial intelligence , mathematics , computer vision , mathematical analysis
This paper proposes a simultaneous algebraic reconstruction technique (SART) based on truncated total variation (truncated TV), called SART-truncated TV algorithm (SART-TTV). Truncated TV is particularly effective in removing unimportant details while preserving significant edges. Moreover, the truncated TV only penalizes part of the gradient of the image, so it can solve the problem of excessive smoothness caused by the classic TV penalizing larger gradient amplitude. In this paper, the classic Shepp-Logan model is simulated and the results of sparse angle reconstruction are compared and analyzed. The results show that the quality of the reconstructed image obtained by the SART-TTV algorithm is the highest.