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Abstract #4187

Automatic segmentation and reconstruction of liver vascular structure on MRI with a deep learning model

Mengsi Li1, Yanjie Hong2, Zhixuan Yu2, Dandan Zheng2, and Jin Wang1
1Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China, 2Shukun (Beijing) Technology Co., Ltd, Beijing, China


The accurate segmentation of liver vascular structure is one of the key components of automated radiological diagnosis. Unfortunately, accurate vessel segmentation in clinical practice usually relies on the manual delineation by radiologists on each slice, which is extremely tedious and time-consuming. We developed and evaluated a new liver vessel segmentation and reconstruction workflow, which consist of a 3D Res-Net, a 2D Dense-Net and a 3D U-net model, allows for automated extraction of the portal vein, hepatic vein and inferior vena cava on 3D contrast enhanced portal venous phase MR images.

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