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Fat‐water separation using a region‐growing algorithm with self‐feeding phasor estimation
Author(s) -
Cheng Chuanli,
Zou Chao,
Liang Changhong,
Liu Xin,
Zheng Hairong
Publication year - 2017
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.26297
Subject(s) - phasor , computer science , pixel , algorithm , data set , disjoint sets , artificial intelligence , mathematics , pattern recognition (psychology) , power (physics) , physics , electric power system , quantum mechanics , combinatorics
Purpose To develop a novel region‐growing algorithm with self‐feeding phasor estimation for robust fat‐water separation. Theory and Methods The proposed seed pixel identification and region‐growing methods were performed independently at different resolutions. Multiple phasor maps were obtained at lower resolutions and then merged into a new seed map, which was used to generate the final phasor map at the finest resolution. The final fat and water images were reconstructed based on this phasor map. The proposed method was compared with traditional region‐growing methods, multiresolution methods, and graph‐cut methods using data from the ISMRM 2012 Challenge. All methods were scored on a scale of 0 to 10000. Results The average score of all 17 data sets from the ISMRM 2012 Challenge was 9928, with 13 of the 17 scores surpassing 9900. The lowest score was 9697 from data set #12; there was no apparent fat‐water swap observed throughout these data sets. Conclusions The self‐feeding mechanism of phasor estimation ensures the reliability of seed pixel selection at the finest resolution. Compared with traditional multiple resolution methods and region‐growing methods, the proposed method is shown to be more robust when applied to disjoint areas and to regions with strong field inhomogeneity. Magn Reson Med 77:2390–2401, 2016. © 2016 International Society for Magnetic Resonance in Medicine