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Abstract #4394

Deep Learning based automatic ROI sampling approach for the measurement of liver PDFF

Xinxin Xu1, Yihuan Wang2, Shuheng Zhang3, Xiang Chen3, Yang Li3, Ke Wu3, Jianmin Yuan4, and Fuhua Yan2
1Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, 2Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, 3United Imaging Healthcare, Shanghai, China, 4Central Research Institute, United Imaging Healthcare, Shanghai, China

Synopsis

Hepatic proton density fat fraction (PDFF) measurement plays an important role in the assessment of chronic diffuse liver diseases, while it is always time consuming and lack of good reproducibility and repeatability. To address this problem, we introduced a five-ROI sampling approach based on a convolutional neural network that provided high dice coefficient (DC) of whole liver segmentation, good correlation and quicker compared with manual operation.

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