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Free‐breathing abdominal MRI improved by repeated k‐t‐subsampling and artifact‐minimization (Re KAM )
Author(s) -
Chu MeiLan,
Chang HingChiu,
Chung HsiaoWen,
Bashir Mustafa R.,
Cai Jing,
Zhang Lei,
Sun Duohua,
Chen Nankuei
Publication year - 2018
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1002/mp.12674
Subject(s) - artifact (error) , computer science , artificial intelligence , computer vision , projection (relational algebra) , image quality , compressed sensing , iterative reconstruction , breathing , minification , medicine , nuclear medicine , algorithm , image (mathematics) , anatomy , programming language
Purpose We report an approach, termed Repeated k‐t‐subsampling and artifact‐minimization (Re KAM ), for removing motion artifacts in free‐breathing abdominal MRI . The method is particularly valuable for challenging patients who may not hold their breath for a long time or have irregular respiratory rate. Methods The Re KAM framework comprises one acquisition module and two reconstruction modules. A fast MRI sequence is used to repeatedly acquire multiple sets of k‐t space data. Motion artifacts are then minimized by two reconstruction modules: (a) a bootstrapping module in k‐t‐space is used to identify a low‐artifact image; (b) a constrained reconstruction module that integrates projection onto convex set ( POCS ) and multiplexed sensitivity encoding ( MUSE ), termed POCSMUSE , is applied to further remove residual artifact. The Re KAM framework is compatible with different pulse sequences, and generally applicable to irregular data sampling patterns in k‐space. Free‐breathing fast spin‐echo MRI data, acquired from healthy volunteers and patients, were used to evaluate the developed Re KAM method. Results Experimental results show that the Re KAM technique can produce high‐quality free‐breathing images with the artifact levels comparable to that of breath‐holding MRI . Conclusion The Re KAM framework improves the quality of free‐breathing abdominal MRI data, and is compatible with various MRI pulse sequences.