Open AccessStatistical iterative reconstruction using adaptive fractional order regularization
Author(s) -
Yi Zhang,
Yan Wang,
Weihua Zhang,
Feng Lin,
Yi-Fei Pu,
Jiliu Zhou
Publication year - 2016
Publication title -
biomedical optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.7.001015
Subject(s) - regularization (linguistics) , iterative reconstruction , computer science , pixel , iterative method , algorithm , mathematical optimization , artificial intelligence , mathematics
In order to reduce the radiation dose of the X-ray computed tomography (CT), low-dose CT has drawn much attention in both clinical and industrial fields. A fractional order model based on statistical iterative reconstruction framework was proposed in this study. To further enhance the performance of the proposed model, an adaptive order selection strategy, determining the fractional order pixel-by-pixel, was given. Experiments, including numerical and clinical cases, illustrated better results than several existing methods, especially, in structure and texture preservation.