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CPTV: Classification by tracking of carotid plaque in ultrasound videos.
Xie, Jiang; Li, Ying; Xu, Xiaochun; Wei, Jinzhu; Li, Haozhe; Wu, Shuo; Chen, Haibing.
Affiliation
  • Xie J; School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China. Electronic address: jiangx@shu.edu.cn.
  • Li Y; School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China.
  • Xu X; School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China.
  • Wei J; School of Medicine, Shanghai University, Shanghai 200444, China.
  • Li H; College of Letters and Science, Department of Statistics and Applied Probability, University of California, Santa Barbara (UCSB), CA 93106, USA.
  • Wu S; Department of Neurology, Luodian Hospital, Baoshan District, Shanghai 201908, China.
  • Chen H; Department of Ultrasound Diagnosis, Luodian Hospital, Baoshan District, Shanghai 201908, China. Electronic address: 13816201797@139.com.
Comput Med Imaging Graph ; 104: 102175, 2023 03.
Article in En | MEDLINE | ID: mdl-36630795
ABSTRACT
The risk assessment of carotid plaque is strongly related to the plaque echo status in ultrasound. However, the echo classification of carotid plaques based on ultrasound remains challenging due to the changes in plaque shape and semantics, along with the complex vascular environment. This study proposed a framework for Classification of Plaque by Tracking Videos (CPTV). To the best of our knowledge, this is the first study on plaque classification by tracking ultrasound video rather than a sonographic view, which achieves accurate localization and stable echo classification. In the tracking task, Multi-scale Decoupling Tracking (MDTrack) module including Multi-scale Dilated Encoder (MDE) and Internal-Exterior Feature Decoupling (IEFD) was proposed to solve the problems caused by shape and semantic variations to achieve accurate plaque localization in ultrasound. In the classification task, the Tracking-assisted 3D Attention (T3D-Attention) module included recombination and 3D-Attention extracted plaque features and echo-related features in the vascular environment. The experiments demonstrated that the performance of CPTV is better than current mainstream tracking and classification methods, indicating that the tracking-assistance classification is a kind of enhancement method with high universality and stability in the plaque in ultrasound.
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Full text: 1 Database: MEDLINE Main subject: Carotid Arteries / Plaque, Atherosclerotic Type of study: Diagnostic_studies / Risk_factors_studies Limits: Humans Language: En Year: 2023 Type: Article

Full text: 1 Database: MEDLINE Main subject: Carotid Arteries / Plaque, Atherosclerotic Type of study: Diagnostic_studies / Risk_factors_studies Limits: Humans Language: En Year: 2023 Type: Article