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Abstract #0541

Robust Fat-water Separation using Binary Decision Tree Algorithm

Hao Peng1,2, Chao Zou2, Wenzhong Liu1, Chuanli Cheng2,3, Yangzi Qiao2, Qian Wan2,3, Changjun Tie2, Xin Liu2, and Hairong Zheng2

1Huazhong University of Science and Technology, Wuhan, China, 2Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences, Shen Zhen, China, 3University of Chinese Academy of Sciences, Beijing, China

Purpose: To propose an robust fat water separation method using binary decision tree algorithm.

Methods: In this paper, a novel fat-water separation algorithm using binary decision tree is proposed. Pixels are firstly clustered into sub-regions. Different from existing region growing algorithms, the proposed method solves the phasor ambiguity problem region by region. The method was tested on data sets from ISMRM 2012 Challenge.

Results:Fat-water separation were successfully achieved by the proposed method in the datasets.

Conclusion: A novel method using binary decision tree algorithm is proposed for robust and accurate water-fat separation.

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