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Corner Detection Based Automatic Segmentation of Bioresorbable Vascular Scaffold Struts in IVOCT Images
Qin, Xianjing1; Yao, Linlin2; Jin, Qinhua3; Jing, Jing3; Chen, Yundai3; Cao, Yihui2; Li, Jianan2; Zhu, Rui2
2018-10-26
Conference Name40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Source Publication40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Volume2018-July
Pages604-607
Conference Date2018-07-18
Conference PlaceHonolulu, HI, United states
PublisherInstitute of Electrical and Electronics Engineers Inc.
Contribution Rank2
AbstractBioresorbable 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 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 priori 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 five pullbacks consisting of 483 images with strut, our novel method achieved an average Dice's coefficient of 0.82 for strut segmentation areas. It concludes that our method can segment struts accurately and robustly. Furthermore, automatic struts malapposition analysis in clinical practice is feasible based on the segmentation results. © 2018 IEEE.
Department瞬态光学技术国家重点实验室
DOI10.1109/EMBC.2018.8512440
Indexed ByEI
ISBN9781538636466
Language英语
ISSN1557170X
EI Accession Number20184906172435
Citation statistics
Document Type会议论文
Identifierhttp://ir.opt.ac.cn/handle/181661/31110
Collection瞬态光学技术国家重点实验室
Affiliation1.Department of Aerospace Biodynamics, Fourth Military Medical University, Xi'an, Shaanxi; 710032, China;
2.Laboratory of Transient Optics and Photonics, Xi'An Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, Shaanxi; 710119, China;
3.Department of Cardiology, Chinese PLA General Hospital, Beijing, China
Recommended Citation
GB/T 7714
Qin, Xianjing,Yao, Linlin,Jin, Qinhua,et al. Corner Detection Based Automatic Segmentation of Bioresorbable Vascular Scaffold Struts in IVOCT Images[C]:Institute of Electrical and Electronics Engineers Inc.,2018:604-607.
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