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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