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基于角点检测的可降解支架轮廓分割算法
Corner Detection-Based Segmentation Algorithm of Bioresorbable Vascular Scaffold Strut Contours

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姚林林 1,2   金琴花 3   荆晶 3   陈韵岱 3   曹一挥 1   李嘉男 1   朱锐 1  
文摘 针对血管内光学相干断层扫描(IVOCT)影像中,使用动态规划(DP)算法进行可降解支架轮廓分割时,分割结果容易受到血液伪影和支架内部断裂的影响,而导致支架轮廓分割准确度不高的问题,利用IVOCT影像中可降解支架具有四边形外观的先验信息,提出一种使用支架的4个角点得到支架轮廓的算法。实验结果显示:所提出的支架轮廓分割算法的平均Dice系数可达到0.88,相较于DP算法提高了0.08;所提出的支架自动分割算法能够实现IVOCT影像中可降解支架的准确分割,且具有较好的稳健性,能更好地在临床应用中辅助医生进行支架贴壁情况分析。
其他语种文摘 According to the prior knowledge about obvious quadrilateral feature of bioresorbable vascular scaffold (BVS) struts in an intravascular optical coherence tomography (IVOCT) image, this study proposes a novel algorithm based on four corners of BVS struts to automatically obtain their contours in the IVOCT imaging system. It solves the problem that dynamic programming (DP) algorithm, which is a contour-based algorithm, is not sufficiently accurate because of the influence of the fractures inside the struts and blood artifacts around the struts. Experimental results show that the proposed algorithm achieves an average Dice's coefficient of 0.88 for the strut segmentation areas, which is increased by approximately 0.08 compared to the result obtained by the DP algorithm. This algorithm can accurately and robustly segment BVS struts in the IVOCT image, and thus it can better assist doctors in the automatic strut malapposition analysis in clinical applications.
来源 光学学报 ,2019,39(7):0715001 【核心库】
DOI 10.3788/AOS201939.0715001
关键词 机器视觉 ; 角点检测 ; 轮廓自动分割 ; 贴壁情况分析 ; 可降解支架 ; 血管内光学相干断层扫描图像
地址

1. 中国科学院西安光学精密机械研究所, 瞬态光学与光子技术国家重点实验室, 陕西, 西安, 710119  

2. 中国科学院大学, 北京, 100049  

3. 中国人民解放军总医院心血管内科, 北京, 100853

语种 中文
文献类型 研究性论文
ISSN 0253-2239
学科 自动化技术、计算机技术
基金 国家科技支撑计划项目
文献收藏号 CSCD:6548044

参考文献 共 23 共2页

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引证文献 2

1 邵晓琦 基于多通道增强融合的自适应液晶屏图像分割 电子测量与仪器学报,2020,34(12):76-84
CSCD被引 1

2 李宁 基于多方向结构张量积的快速角点检测算法 激光与光电子学进展,2021,58(20):2015005
CSCD被引 1

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