Abstract #0541

Robust Fat-water Separation using Binary Decision Tree Algorithm

Hao Peng^1,2, Chao Zou², Wenzhong Liu¹, Chuanli Cheng^2,3, Yangzi Qiao², Qian Wan^2,3, 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.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.