ShanghaiTech University Knowledge Management System
| Investigation of Interactive Segmentation for Bifurcation of Carotid Artery on 3D Ultrasound Image Volume | |
| 2023-11-07 | |
| 会议录名称 | 2023 IEEE INTERNATIONAL ULTRASONICS SYMPOSIUM (IUS)
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| ISSN | 1948-5719 |
| 发表状态 | 已发表 |
| DOI | 10.1109/IUS51837.2023.10306567 |
| 摘要 | Ultrasound (US) imaging is widely used to diagnose carotid atherosclerosis (CA) caused by carotid plaque since it is non-invasive and economic. Current automatic plaque segmentation method based on deep learning shows high accuracy on common carotid artery but poor performance at the bifurcation of carotid artery. This study proposes an interactive segmentation algorithm that accurately segments carotid plaque at the bifurcation using limited user interaction. The algorithm utilizes a 3D ultrasound imaging system and a 3D U-net segmentation network to obtain masks of media-adventitia boundary (MAB) and lumen-intima boundary (LIB). The results demonstrate improved accuracy over conventional automatic segmentation methods with DSC /HD95 values of 0.952/0.964 for MAB and 0.937/1.068 for LIB, respectively. The proposed algorithm shows potential of clinical implications for the diagnosis of carotid atherosclerosis at bifurcation. © 2023 IEEE. |
| 会议录编者/会议主办者 | IEEE ; IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society (UFFC) |
| 关键词 | 3D Ultrasound Imaging Carotid Artery Bifurecation Segmentation Atherosclerosis |
| 会议名称 | 2023 IEEE International Ultrasonics Symposium, IUS 2023 |
| 会议地点 | Montreal, QC, Canada |
| 会议日期 | 3-8 Sept. 2023 |
| URL | 查看原文 |
| 收录类别 | EI |
| 语种 | 英语 |
| 出版者 | IEEE Computer Society |
| EI入藏号 | 20234915175329 |
| EI主题词 | Ultrasonic imaging |
| EISSN | 1948-5727 |
| EI分类号 | 461.4 Ergonomics and Human Factors Engineering ; 746 Imaging Techniques |
| 原始文献类型 | Conference article (CA) |
| 来源库 | IEEE |
| 文献类型 | 会议论文 |
| 条目标识符 | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/348749 |
| 专题 | 信息科学与技术学院 信息科学与技术学院_PI研究组_郑锐组 信息科学与技术学院_硕士生 信息科学与技术学院_博士生 |
| 通讯作者 | Zhang, Fayi; Chen, Man; Zheng, Rui |
| 作者单位 | 1.ShanghaiTech University, School of Information Science and Technology, Shanghai, China 2.Shanghai Jiao Tong University, School of Medicine, Tongren Hospital, Shanghai, China 3.Shanghai Engineering Research Center of Intelligent Vision and Imaging, Shanghai, China |
| 第一作者单位 | 信息科学与技术学院 |
| 通讯作者单位 | 信息科学与技术学院 |
| 第一作者的第一单位 | 信息科学与技术学院 |
| 推荐引用方式 GB/T 7714 | Zhang, Fayi,Li, Jiawen,Huang, Yunqiang,et al. Investigation of Interactive Segmentation for Bifurcation of Carotid Artery on 3D Ultrasound Image Volume[C]//IEEE, IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society (UFFC):IEEE Computer Society,2023. |
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