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Automated coronary artery analysis system in 3D CTA images

机译:3D CTA图像中的自动冠状动脉分析系统

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This paper presents an automated computer assistant system for segmentation and quantification of the coronary arteries in 3D contrast enhanced computed tomography angiography (CTA). To the best of our knowledge, no commercially available software package permits fully automated detection and assessment of atherosclerotic stenosis so far. Therefore, in clinical practice, the evaluation of the coronary CT studies is accomplished by radiologists, which is obviously a tedious and time consuming task, since it usually involves hundreds of axial cross sectional CT images to be examined. In the proposed system, the main branches of the coronary arteries are firstly extracted from the volume datasets by employing a regional statistic based active contours method. Next, calcified voxels are detected in the within the coronary vessels and removed. The centreline of the coronaries is extracted by mesh contraction algorithm in the following step. Finally, we compute the circularity and the convex hull deficiency of the cross sections at specific locations along the coronary arteries, which are then used to automatically detect and identify the presence of calcified stenosis
机译:本文介绍了一种自动计算机辅助系统,用于在3D造影剂增强型CT血管造影(CTA)中对冠状动脉进行分割和量化。据我们所知,到目前为止,尚无可商购的软件包允许对动脉粥样硬化狭窄进行全自动检测和评估。因此,在临床实践中,冠状动脉CT研究的评估是由放射科医生完成的,这显然是一项繁琐且耗时的任务,因为它通常涉及数百个要检查的轴向横截面CT图像。在所提出的系统中,首先通过使用基于区域统计的主动轮廓方法从体积数据集中提取冠状动脉的主要分支。接下来,在冠状血管内检测到钙化的体素并将其去除。在接下来的步骤中,通过网格收缩算法提取冠状动脉的中心线。最后,我们计算出沿冠状动脉特定位置的横截面的圆形度和凸壳缺陷,然后将其用于自动检测和识别钙化狭窄的存在

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