An effective automatic segmentation of abdominal adipose tissue using a convolution neural network.

Journal: Diabetes & metabolic syndrome
PMID: 35995029

Abstract

BACKGROUND AND AIMS: Computer-aided diagnosis and prognosis rely heavily on fully automatic segmentation of abdominal fat tissue using Emission Tomography images. The identification of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) in abdomen fat faces two main challenges: (1) the great difficulties in comparison to multi-stage semantic segmentation (VAT and SAT), and (2) the subtle differences due to the high similarity of the two classes in abdomen fat and complicated VAT distribution.

Authors

  • Carine Micomyiza
    School of Computer Science and Engineering, Central South University, Changsha, 410083, China.
  • Beiji Zou
    School of Information Science and Engineering, Central South University, Changsha, China; Mobile Health Ministry of Education-China Mobile Joint Laboratory, Changsha, China.
  • Yang Li
    Occupation of Chinese Center for Disease Control and Prevention, Beijing, China.

Keywords

External Resources

Popular Topics
Recent Journals