Advanced Ultrasound in Diagnosis and Therapy ›› 2023, Vol. 7 ›› Issue (2): 140-151.doi: 10.37015/AUDT.2023.230015

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Advances in Intelligent Segmentation and 3D/4D Reconstruction of Carotid Ultrasound Imaging

Cancan Cui, MDa,1, Zhaojun Li, PhDb,1, Yanping Lin, PhDa,*()   

  1. a School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, PR China
    b Department of Ultrasound, Shanghai General Hospital Jiading Branch, Shanghai Jiao tong University School of Medicine, Shanghai, PR China
  • Received:2023-03-29 Revised:2023-04-30 Accepted:2023-05-04 Online:2023-06-30 Published:2023-04-27
  • Contact: Yanping Lin, PhD,
  • About author:First author contact:

    1Cancan Cui and Zhaojun Li have contributed equally to this study.


Cardiovascular disease (CVD) is one of the ten leading causes of death worldwide. Atherosclerotic disease, which can lead to myocardial infarction and stroke, is the main cause of CVD. The two main ultrasound image phenotypes used to monitor atherosclerotic load are carotid intima-media thickness (IMT) and plaque area (PA). Early segmentation and measurement methods were based on manual or threshold segmentation, snake models, etc. Usually, these methods are semi-automatic and have poor repeatability and accuracy. Segmentation of the carotid intima-media complex (IMC) and plaque in ultrasound based on artificial intelligence can achieve good accuracy. Compared with two-dimensional ultrasound, three-dimensional/four-dimensional ultrasound can provide spatial dynamic vascular information, which is helpful for doctors to evaluate. This study reviews the progress of artificial intelligence (AI) segmentation methods based on machine learning (ML) and deep learning (DL) used in the segmentation of the IMC and plaque as well as the 3D / 4D reconstruction of carotid ultrasound.

Key words: Intima-media thickness; Carotid artery plaque; Image segmentation; 3D/4D ultrasound reconstruction; Artificial intelligence