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A Framework for Automatic Detection of Lumen-Endothelium Border in Intracoronary OCT Image Sequences

机译:冠状动脉内OCT图像序列中管腔-内皮边界的自动检测框架

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Intracoronary optical coherence tomography (OCT) is increasingly being used for real-time visualization of coronary arteries aiming to help in the identification of high-risk atherosclerotic plaques associated with geometrical and morphological features of the arterial wall. This paper presents a framework towards the automatic detection of the inner wall of the coronary artery (lumen-endothelium border) in intracoronary OCT image sequences by employing a multi-step image processing method. The major focus of this work was to address difficult cases that are frequently met in intracoronary OCT, e.g. images with small/big branches, multiple branches, blood presence, calcifications, artifacts, etc. We present each step employed and the results obtained both in qualitative and quantitative terms. The proposed segmentation algorithm has been proven very efficient in the majority of the examined cases.
机译:冠状动脉内光学相干断层扫描(OCT)越来越多地用于实时显示冠状动脉,旨在帮助识别与动脉壁几何和形态学特征相关的高危动脉粥样硬化斑块。本文提出了一种利用多步图像处理方法在冠状动脉内OCT图像序列中自动检测冠状动脉内壁(管腔-内皮边界)的框架。这项工作的主要重点是解决冠状动脉内OCT中经常遇到的疑难病例,例如,具有小/大分支、多分支、血液存在、钙化、伪影等的图像。我们从定性和定量两个方面介绍了所采用的每个步骤和获得的结果。所提出的分割算法在大多数被检查的案例中被证明是非常有效的。

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