Spatial feature fusion convolutional network for liver and liver tumor segmentation from CT images.

Journal: Medical physics
Published Date: Nov 27, 2020

Abstract

PURPOSE: The accurate segmentation of liver and liver tumors from CT images can assist radiologists in decision-making and treatment planning. The contours of liver and liver tumors are currently obtained by manual labeling, which is time-consuming and subjective. Computer-aided segmentation methods have been widely used in the segmentation of liver and liver tumors. However, due to the diversity of shape, volume, and image intensity, the segmentation is still a difficult task. In this study, we present a Spatial Feature Fusion Convolutional Network (SFF-Net) to automatically segment liver and liver tumors from CT images.

Authors

  • Tianyu Liu
    Department of Automation, Tsinghua University,Beijing, China.
  • Junchi Liu
    Medical Imaging Research Center & Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, 60616, USA.
  • Yan Ma
    Medical School of Chinese PLA, 100853 Beijing, China.
  • Jiangping He
    School of Science and Engineering, Lanzhou University of Finance and Economics, Lanzhou, Gansu, China.
  • Jincang Han
    Department of Electronic Engineering, Lanzhou University of Finance and Economics, Lanzhou, 730020, China.
  • Xiaoyang Ding
    Department of Electronic Engineering, Lanzhou University of Finance and Economics, Lanzhou, 730020, China.
  • Chin-Tu Chen
    Radiology, The University of Chicago, Chicago, IL.

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