Dissected aorta segmentation using convolutional neural networks.

Journal: Computer methods and programs in biomedicine
Published Date: Nov 1, 2021

Abstract

BACKGROUND AND OBJECTIVE: Aortic dissection is a severe cardiovascular pathology in which an injury of the intimal layer of the aorta allows blood flowing into the aortic wall, forcing the wall layers apart. Such situation presents a high mortality rate and requires an in-depth understanding of the 3-D morphology of the dissected aorta to plan the right treatment. An accurate automatic segmentation algorithm is therefore needed.

Authors

  • Tianling Lyu
    Laboratory of Image Science and Technology, Southeast University, Nanjing, Jiangsu, China; Stanford Cancer Center, 875 Blake Wilbur Dr, Palo Alto, CA, US.
  • Guanyu Yang
    Laboratory of Image Science and Technology, School of Computer Science and Engineering, Southeast University, Nanjing, China; Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Nanjing, China; Centre de Recherche en Information Biomedicale Sino-Francais (LIA CRIBs), Rennes, France.
  • Xingran Zhao
    Laboratory of Imaging Science and Technology, Southeast University, Nanjing, China.
  • Huazhong Shu
    Lab of Image Science and Technology, School of Computer Science and Engineering, Southeast University, Nanjing, China. shu.list@seu.edu.cn.
  • Limin Luo
  • Duanduan Chen
    Phage Research Center of Liaocheng University, Liaocheng, China.
  • Jiang Xiong
    Key Laboratory of Intelligent Information Processing and Control, Chongqing Municipal Institutions of Higher Education, Chongqing Three Gorges University, Chongqing 40044, China.
  • Jian Yang
    Drug Discovery and Development Research Group, College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK, Canada.
  • Shuo Li
    Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Jean-Louis Coatrieux
  • Yang Chen
    Orthopedics Department of the First Affiliated Hospital of Tsinghua University, Beijing, China.

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