Automatic liver segmentation using 3D convolutional neural networks with a hybrid loss function.

Journal: Medical physics
Published Date:

Abstract

PURPOSE: Automatic liver segmentation from abdominal computed tomography (CT) images is a fundamental task in computer-assisted liver surgery programs. Many liver segmentation algorithms are very sensitive to fuzzy boundaries and heterogeneous pathologies, especially when the data are scarce. To solve these problems, we propose an automatic liver segmentation framework based on three-dimensional (3D) convolutional neural networks with a hybrid loss function.

Authors

  • Man Tan
    The School of Mathematical Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China.
  • Fa Wu
    School of Mathematical Sciences, Zhejiang University, Hangzhou 310027, China.
  • Dexing Kong
    School of Mathematical Sciences, Zhejiang University, Hangzhou 310027, China. Electronic address: dkong@zju.edu.cn.
  • Xiongwei Mao
    The Radiology Department, The Hospital of Zhejiang University, Hangzhou, Zhejiang, 310058, China.