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

机译:ICTORONARY OCT图像序列中腔内皮边界自动检测框架

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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:颅内光学相干断层扫描(OCT)越来越多地用于冠状动脉的实时可视化,旨在帮助鉴定与动脉壁的几何和形态特征相关的高危动脉粥样硬化斑块。本文通过采用多步骤图像处理方法,呈现朝向颅内型OCT图像序列中冠状动脉(内腔内皮边界)内壁的框架。这项工作的主要焦点是解决常见案件的困难案例,例如,在Intracoronary Oct中,例如,具有小/大分支,多个分支,血液存在,钙化,伪影等的图像。我们展示了所用的每个步骤和在定性和定量术语中获得的结果。所提出的分割算法在大多数检查病例中被证明非常有效。

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