Segmentation and visualization of left atrium through a unified deep learning framework.

Journal: International journal of computer assisted radiology and surgery
Published Date: Apr 1, 2020

Abstract

PURPOSE: Left atrium segmentation and visualization serve as a fundamental and crucial role in clinical analysis and understanding of atrial fibrillation. However, most of the existing methods are directly transmitting information, which may cause redundant information to be passed to affect segmentation performance. Moreover, they did not further consider atrial visualization after segmentation, which leads to a lack of understanding of the essential atrial anatomy.

Authors

  • Xiuquan Du
    Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, ‡School of Computer Science and Technology, and §Center of Information Support & Assurance Technology, Anhui University , Hefei, 230601 Anhui, China.
  • Susu Yin
  • Renjun Tang
  • Yueguo Liu
    School of Computer Science and Technology, Anhui University, Anhui, China.
  • Yuhui Song
    School of Computer Science and Technology, Anhui University, Hefei, China.
  • Yanping Zhang
    Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, ‡School of Computer Science and Technology, and §Center of Information Support & Assurance Technology, Anhui University , Hefei, 230601 Anhui, China.
  • Heng Liu
    Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D, College of Pharmacy, Dali University, Dali, Yunnan, PR China; National-Local Joint Engineering Research Center of Entomoceutics, Dali, PR China.
  • Shuo Li
    Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

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