Real-time carotid plaque recognition from dynamic ultrasound videos based on artificial neural network.

Journal: Ultraschall in der Medizin (Stuttgart, Germany : 1980)
PMID: 38113893

Abstract

PURPOSE: Carotid ultrasound allows noninvasive assessment of vascular anatomy and function with real-time display. Based on the transfer learning method, a series of research results have been obtained on the optimal image recognition and analysis of static images. However, for carotid plaque recognition, there are high requirements for self-developed algorithms in real-time ultrasound detection. This study aims to establish an automatic recognition system, Be Easy to Use (BETU), for the real-time and synchronous diagnosis of carotid plaque from ultrasound videos based on an artificial neural network.

Authors

  • Yao Wei
    Department of Pharmaceutical Sciences, University of Basel, Klingelbergstrasse 50, 4056 Basel, Switzerland.
  • Bin Yang
    School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, PR China. Electronic address: yangbin@dlut.edu.cn.
  • Ling Wei
    College of Foreign Languages, Chongqing College of Mobile Communication, Chongqing, China.
  • Jun Xue
    Department of Echocardiography, China Meitan General Hospital, Beijing, China.
  • Yicheng Zhu
    Research School of Biology, The Australian National University, Canberra, Australian Capital Territory 2601, Australia yicheng.zhu@anu.edu.au gavin.huttley@anu.edu.au.
  • Jianchu Li
    Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730, China.
  • Mingwei Qin
  • Shuyang Zhang
  • Qing Dai
  • Meng Yang

Keywords

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