Open AccessFast iterative contourlet thresholding for compressed sensing MRI
Author(s) -
Hao Wangli,
Li Jianwu,
Qu Xiaobo,
Dong Zhengchao
Publication year - 2013
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2013.1483
Subject(s) - contourlet , compressed sensing , thresholding , computer science , computation , artificial intelligence , sparse approximation , iterative method , representation (politics) , algorithm , pattern recognition (psychology) , benchmark (surveying) , iterative reconstruction , image (mathematics) , wavelet transform , wavelet , geodesy , politics , political science , law , geography
Proposed is the use of the contourlet as a sparse transform which is combined with the fast iterative shrinkage/threshold algorithm (FISTA) for compressed sensing magnetic resonance imaging reconstruction. The proposed method not only inherits the simplicity and effectiveness of the original FISTA but also has the sparse curve representation ability of the contourlet. Simulation results validate the superior performance of the proposed method in terms of reconstruction accuracy and computation time.