Fully automatic segmentation of type B aortic dissection from CTA images enabled by deep learning.

Journal: European journal of radiology
Published Date:

Abstract

PURPOSE: This study sought to establish a robust and fully automated Type B aortic dissection (TBAD) segmentation method by leveraging the emerging deep learning techniques.

Authors

  • Long Cao
    Department of Vascular and Endovascular Surgery, Chinese PLA General Hospital, Beijing, PR China. Electronic address: caolong@301hospital.com.cn.
  • Ruiqiong Shi
    Institute of Information Science, Beijing Jiaotong University, Beijing, PR China; Huiying Medical Technology Co., Ltd., Dongsheng Science and Technology Park, Beijing, PR China. Electronic address: Ruiqiong_Shi@bjtu.edu.cn.
  • Yangyang Ge
    Department of Vascular and Endovascular Surgery, Chinese PLA General Hospital, Beijing, PR China. Electronic address: geyangyang@301hospital.com.cn.
  • Lei Xing
    Department of Radiation Oncology, Stanford University, CA, USA.
  • Panli Zuo
    Huiying Medical Technology Co., Ltd., Dongsheng Science and Technology Park, Beijing, PR China. Electronic address: zuopanli@huiyihuiying.com.
  • Yan Jia
    Department of Gastroenterology, the 7Medical Center of PLA General Hospital, Beijing, China.
  • Jie Liu
    School of Bioscience and Bioengineering, South China University of Technology, Guangzhou, China.
  • Yuan He
    Department of Vascular and Endovascular Surgery, Chinese PLA General Hospital, Beijing, PR China. Electronic address: heyuan@301hospital.com.cn.
  • Xinhao Wang
    Department of Vascular and Endovascular Surgery, Chinese PLA General Hospital, Beijing, PR China. Electronic address: wangxinhao@301hospital.com.cn.
  • Shaoliang Luan
    Department of Vascular and Endovascular Surgery, Chinese PLA General Hospital, Beijing, PR China. Electronic address: luanshaoliang@126.com.
  • Xiangfei Chai
    Huiying Medical Technology Co., Ltd., Dongsheng Science and Technology Park, Beijing, PR China. Electronic address: chaixiangfei@huiyihuiying.com.
  • Wei Guo
    Emergency Department, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.