Abstract #2989

A Two-Stage Deep Learning Model for Accurate Vessel Segmentation and Reconstruction in the MRI of Live

Xu Luo^1,2, Ailian Liu³, Yu Yao^1,2, Ying Zhao³, Zhebin Chen^1,2, Meng Dou^1,2, and Han Wen^1,2

¹Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu, China, ²University of Chinese Academy of Sciences, Beijing, China, ³Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China

The deep learning technology was used on the segmentation automatically and reconstruction of the intrahepatic portal vein to get its volume and three-dimensional spatial position information. The results showed that the dice accuracy was 83.32% in the training and 75.89% in the test set among 12 cases. The current study demonstrated the volume of intrahepatic vessels and 3D spatial location information can be obtained by the tow-stage deep learning model and it can be applied in promising clinical effectively.

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