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首页> 外文会议>IEEE International Symposium on Biomedical Imaging >AUTOMATIC IDENTIFICATION OF SIDE BRANCH AND MAIN VASCULAR MEASUREMENTS IN INTRAVASCULAR OPTICAL COHERENCE TOMOGRAPHY IMAGES
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AUTOMATIC IDENTIFICATION OF SIDE BRANCH AND MAIN VASCULAR MEASUREMENTS IN INTRAVASCULAR OPTICAL COHERENCE TOMOGRAPHY IMAGES

机译：侧枝自动识别和血管外光相干断层扫描图像中的侧枝和主要血管测量

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Automatic identification of side branch and main vascular measurements in IVOCT images take critical roles in pre-interventional decision making for coronary artery disease treatment. Very little works have been presented on these tasks. In this paper, we proposed a novel side branch identification algorithm which utilizes a newly defined global curvature feature to identify the ostium of side branch. Based on identification results, the main vascular can be segmented automatically for measurements. In the measurement of main vascular, the diameter of maximum inscribed circle of main vascular is proposed for the first time, which could be helpful in stent size decision. The qualitative and quantitative validation results demonstrated that the proposed algorithm is effective and accurate.
机译：IVOCT图像中的侧支分支的自动识别和主要血管测量在冠状动脉疾病治疗前介入决策中对临床职务作用。这些任务已经介绍了很少的作品。在本文中，我们提出了一种新颖的侧分支识别算法，其利用新定义的全局曲率特征来识别侧分支的竖置。基于鉴定结果，可以自动分割主血管进行测量。在主要血管的测量中，首次提出了主要血管的最大刻录圆的直径，这可能有助于支架规模决定。定性和定量验证结果表明，所提出的算法是有效准确的。

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