Combining artificial intelligence assisted image segmentation and ultrasound based radiomics for the prediction of carotid plaque stability.

Journal: BMC medical imaging

PMID: 40098096

Abstract

PURPOSE: Utilizing artificial intelligence (AI) technology for the segmentation of plaques on ultrasound images to evaluate the stability of carotid artery plaques and analyze its diagnostic accuracy in differentiating vulnerable plaques from stable ones.

Authors

Jiajia Song

Department of Physical Diagnosis, Affiliated Nanjing Brain Hospital, Nanjing Medical University, No. 264, Guangzhou Road, Gulou District, Nanjing, Jiangsu, 210008, China.
Liwen Zou

Department of Mathematics, Nanjing University, Nanjing, China.
Yu Li

Department of Public Health, Shihezi University School of Medicine, 832000, China.
Xiaoyin Wang

Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, 310058, China.
Junlan Qiu

Department of Ultrasound Medicine, Affiliated Hospital of Medical School, Nanjing Drum Tower Hospital, Nanjing University, Nanjing, 210000, China. weiyumo@163.com.
Kailin Gong

Department of Physical Diagnosis, Affiliated Nanjing Brain Hospital, Nanjing Medical University, No. 264, Guangzhou Road, Gulou District, Nanjing, Jiangsu, 210008, China. kelly3328218@163.com.

Keywords

Aged Artificial Intelligence Carotid Arteries Carotid Stenosis Female Humans Image Interpretation, Computer-Assisted Ischemic Stroke Male Middle Aged Plaque, Atherosclerotic Radiomics Retrospective Studies ROC Curve Sensitivity and Specificity Support Vector Machine Ultrasonography, Doppler, Color

External Resources

View on PubMed Access via DOI PubMed (40098096)

Combining artificial intelligence assisted image segmentation and ultrasound based radiomics for the prediction of carotid plaque stability.

Abstract

Authors

Keywords

External Resources

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