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Fully automated side branch detection in intravascular optical coherence tomography pullback runs

机译:血管内光学相干断层扫描回撤运行中的全自动侧枝检测

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摘要

Side branches in the atherosclerotic lesion region are important as they highly influence the treatment strategy selection and optimization. Moreover, they are reliable landmarks for image registration. By providing high resolution delineation of coronary morphology, intravascular optical coherence tomography (IVOCT) has been increasingly used for side branch analysis. This paper presents a fully automated method to detect side branches in IVOCT images, which relies on precise segmentation of the imaging catheter, the protective sheath, the guide wire and the lumen. 25 in-vivo data sets were used for validation. The intraclass correlation coefficient between the algorithmic results and manual delineations for the imaging catheter, the protective sheath and the lumen contour positions was 0.997, 0.949 and 0.974, respectively. All the guide wires were detected correctly and the Dice’s coefficient of the shadow regions behind the guide wire was 0.97. 94.0% of 82 side branches were detected with 5.0% false positives and the Dice’s coefficient of the side branch size was 0.85. In conclusion, the presented method has been demonstrated to be accurate and robust for side branch analysis.
机译:动脉粥样硬化病变区域的侧支非常重要,因为它们会极大地影响治疗策略的选择和优化。此外,它们是图像配准的可靠​​地标。通过提供冠状动脉形态的高分辨率描绘,血管内光学相干断层扫描(IVOCT)已越来越多地用于侧支分析。本文提出了一种全自动的方法来检测IVOCT图像中的侧支,该方法依赖于成像导管,保护套,导丝和内腔的精确分割。使用25个体内数据集进行验证。成像导管,保护套和管腔轮廓位置的算法结果与手动描述之间的类内相关系数分别为0.997、0.949和0.974。正确检测了所有导线,导线后面阴影区域的Dice系数为0.97。检测到82个侧枝中的94.0%带有5.0%的假阳性,并且Dice的侧枝大小系数为0.85。总之,已经证明了所提出的方法对于侧枝分析是准确且鲁棒的。

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