Deep learning-based automatic segmentation of images in cardiac radiography: A promising challenge.

Journal: Computer methods and programs in biomedicine
Published Date:

Abstract

BACKGROUND: Due to the advancement of medical imaging and computer technology, machine intelligence to analyze clinical image data increases the probability of disease prevention and successful treatment. When diagnosing and detecting heart disease, medical imaging can provide high-resolution scans of every organ or tissue in the heart. The diagnostic results obtained by the imaging method are less susceptible to human interference. They can process numerous patient information, assist doctors in early detection of heart disease, intervene and treat patients, and improve the understanding of heart disease symptoms and clinical diagnosis of great significance. In a computer-aided diagnosis system, accurate segmentation of cardiac scan images is the basis and premise of subsequent thoracic function analysis and 3D image reconstruction.

Authors

  • Yucheng Song
    School of Computer Science and Engineering, Central South University, Changsha, China.
  • Shengbing Ren
    School of Computer Science and Engineering, Central South University, Changsha, China.
  • Yu Lu
    Faw-volkswagen Automative Co., Changchun, China.
  • Xianghua Fu
    College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China. Electronic address: fuxianghua@sztu.edu.cn.
  • Kelvin K L Wong
    School of Medicine, Western Sydney University, Sydney, Australia. Electronic address: kelvin.wong@westernsydney.edu.au.