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Image reconstruction algorithm for motion insensitive MR Fingerprinting (MRF): MORF
Author(s) -
Mehta Bhairav Bipin,
Ma Dan,
Pierre Eric Yann,
Jiang Yun,
Coppo Simone,
Griswold Mark Alan
Publication year - 2018
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.27227
Subject(s) - artificial intelligence , computer science , computer vision , robustness (evolution) , motion (physics) , iterative reconstruction , motion estimation , ground truth , metric (unit) , data consistency , pattern recognition (psychology) , algorithm , biochemistry , chemistry , operations management , economics , gene , operating system
Purpose The purpose of this study is to increase the robustness of MR fingerprinting (MRF) toward subject motion. Methods A novel reconstruction algorithm, MOtion insensitive MRF (MORF), was developed, which uses an iterative reconstruction based retrospective motion correction approach. Each iteration loops through the following steps: pattern recognition, metric based identification of motion corrupted frames, registration based motion estimation, and motion compensated data consistency verification. The proposed algorithm was validated using in vivo 2D brain MRF data with retrospective in‐plane motion introduced at different stages of the acquisition. The validation was performed using qualitative and quantitative comparisons between results from MORF, the iterative multi‐scale (IMS) algorithm, and with the IMS results using data without motion for a ground truth comparison. Additionally, the MORF algorithm was evaluated in prospectively motion corrupted in vivo 2D brain MRF datasets. Results For datasets corrupted by in‐plane motion both prospectively and retrospectively, MORF noticeably reduced motion artifacts compared with iterative multi‐scale and closely resembled the results from data without motion, even when ∼54% of data was motion corrupted during different parts of the acquisition. Conclusions MORF improves the insensitivity of MRF toward rigid‐body motion occurring during any part of the MRF acquisition.