A Video-based Automated Tracking and Analysis System of Plaque Burden in Carotid Artery Using Deep Learning: A Comparison with Senior Sonographers.

Journal: Current medical imaging
PMID: 38639284

Abstract

BACKGROUND AND OBJECTIVE: The incidence of stroke is rising, and it is the second major cause of mortality and the third leading cause of disability around the globe. The goal of this study was to rapidly and accurately identify carotid plaques and automatically quantify plaque burden using our automated tracking and segmentation US-video system.

Authors

  • Wenjing Gao
    Department of Ultrasound, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen 518020, Guangdong, China.
  • Mengmeng Liu
    Department of First Hospital, Jilin University, Changchun, China.
  • Jinfeng Xu
    Department of Ultrasound, The Second Clinical Medical Collegeļ¼ŒJinan University, Guangdong, China.
  • Shaofu Hong
    Department of Ultrasound, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen 518020, Guangdong, China.
  • Jiayi Chen
    College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang 310058, China. dylee@zju.edu.cn.
  • Chen Cui
    Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai, 201203, China; University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing, 100049, China.
  • Siyuan Shi
    Department of Ultrasound, The Second Clinical Medical Collegeļ¼ŒJinan University, Guangdong, China.
  • Yinghui Dong
    Department of Ultrasound, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen 518020, Guangdong, China.
  • Di Song
    Department of Ultrasound, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen 518020, Guangdong, China.
  • Fajin Dong
    Department of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen, China.

Keywords

External Resources

Popular Topics
Recent Journals