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Corners Detection for Bioresorbable Vascular Scaffolds Segmentation in IVOCT Images
Yao, Linlin1,2; Cao, Yihui1,3; Jin, Qinhua4; Jing, Jing4; Chen, Yundai4; Li, Jianan1,3; Zhu, Rui1,3
2018
会议名称21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018
会议录名称Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 - 21st International Conference, 2018, Proceedings
卷号11073 LNCS
页码552-560
会议日期2018-09-16
会议地点Granada, Spain
出版者Springer Verlag
产权排序1
摘要

Bioresorbable Vascular scaffold (BVS) is a promising type of stent in percutaneous coronary intervention. Struts apposition assessment is important to ensure the safety of implanted BVS. Currently, BVS struts apposition analysis in 2D IVOCT images still depends on manual delineation of struts, which is labor intensive and time consuming. Automatic struts segmentation is highly desired to simplify and speed up quantitative analysis. However, it is difficult to segment struts accurately based on the contour, due to the influence of fractures inside strut and blood artifacts around strut. In this paper, a novel framework of automatic struts segmentation based on four corners is introduced, in which prior knowledge is utilized that struts have obvious feature of box-shape. Firstly, a cascaded AdaBoost classifier based on enriched haar-like features is trained to detect struts corners. Then, segmentation result can be obtained based on the four detected corners of each strut. Tested on the same five pullbacks consisting of 480 images with strut, our novel method achieved an average Dice’s coefficient of 0.85 for strut segmentation areas, which is increased by about 0.01 compared to the state-of-the-art. It concludes that our method can segment struts accurately and robustly and has better performance than the state-of-the-art. Furthermore, automatic struts malapposition analysis in clinical practice is feasible based on the segmentation results. © 2018, Springer Nature Switzerland AG.

作者部门瞬态光学技术国家重点实验室
DOI10.1007/978-3-030-00937-3_63
收录类别EI
ISBN号9783030009366
语种英语
ISSN号03029743;16113349
EI入藏号20183905872897
引用统计
文献类型会议论文
条目标识符http://ir.opt.ac.cn/handle/181661/30661
专题瞬态光学技术国家重点实验室
通讯作者Chen, Yundai
作者单位1.State Key Laboratory of Transient Optics and Photonics, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, China;
2.University of Chinese Academy of Sciences, Beijing, China;
3.Shenzhen Vivolight Medical Device & Technology Co., Ltd., Shenzhen, China;
4.Department of Cardiology, Chinese PLA General Hospital, Beijing, China
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Yao, Linlin,Cao, Yihui,Jin, Qinhua,et al. Corners Detection for Bioresorbable Vascular Scaffolds Segmentation in IVOCT Images[C]:Springer Verlag,2018:552-560.
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