Automatic abdominal multi-organ segmentation using deep convolutional neural network and time-implicit level sets.

Journal: International journal of computer assisted radiology and surgery
Published Date: Nov 24, 2016

Abstract

PURPOSE: Multi-organ segmentation from CT images is an essential step for computer-aided diagnosis and surgery planning. However, manual delineation of the organs by radiologists is tedious, time-consuming and poorly reproducible. Therefore, we propose a fully automatic method for the segmentation of multiple organs from three-dimensional abdominal CT images.

Authors

  • Peijun Hu
    School of Mathematical Sciences, Zhejiang University, Hangzhou, 310027, China.
  • Fa Wu
    School of Mathematical Sciences, Zhejiang University, Hangzhou 310027, China.
  • Jialin Peng
    College of Computer Science and Technology, Huaqiao University, Xiamen, 361021, China.
  • Yuanyuan Bao
    School of Mathematical Sciences, Zhejiang University, Hangzhou, 310027, China.
  • Feng Chen
    Department of Integrated Care Management Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
  • Dexing Kong
    School of Mathematical Sciences, Zhejiang University, Hangzhou 310027, China. Electronic address: dkong@zju.edu.cn.

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