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基于最小代价路径的 CT 冠状动脉造影图像中冠状动脉中心线提取。

Coronary centerline extraction from CT coronary angiography images using a minimum cost path approach.

机构信息

Department of Medical Informatics and Department of Radiology, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands.

出版信息

Med Phys. 2009 Dec;36(12):5568-79. doi: 10.1118/1.3254077.

Abstract

PURPOSE

The application and large-scale evaluation of minimum cost path approaches for coronary centerline extraction from computed tomography coronary angiography (CTCA) data and the development and evaluation of a novel method to reduce the user-interaction time.

METHODS

A semiautomatic method based on a minimum cost path approach is evaluated for two different cost functions. The first cost function is based on a frequently used vesselness measure and intensity information, and the second is a recently proposed cost function based on region statistics. User interaction is minimized to one or two mouse clicks distally in the coronary artery. The starting point for the minimum cost path search is automatically determined using a newly developed method that finds a point in the center of the aorta in one of the axial slices. This step ensures that all computationally expensive parts of the algorithm can be precomputed.

RESULTS

The performance of the aorta localization procedure was demonstrated by a success rate of 100% in 75 images. The success rate and accuracy of centerline extraction was quantitatively evaluated on 48 coronary arteries in 12 images by comparing extracted centerlines with a manually annotated reference standard. The method was able to extract 88% and 47% of the vessel center-lines correctly using the vesselness/intensity and region statistics cost function, respectively. For only the proximal part of the vessels these values were 97% and 86%, respectively. Accuracy of centerline extraction, defined as the average distance from correctly automatically extracted parts of the centerline to the reference standard, was 0.64 mm for the vesselness/intensity and 0.51 mm for the region statistics cost function. The interobserver variability was 99% for the success rate measure and 0.42 mm for the accuracy measure. Qualitative evaluation using the best performing cost function resulted in successful centerline extraction for 233 out of the 252 coronaries (92%) in 63 additional CTCA images.

CONCLUSIONS

The presented results, in combination with minimal user interaction and low computation time, show that minimum cost path approaches can effectively be applied as a preprocessing step for subsequent analysis in clinical practice and biomedical research.

摘要

目的

应用最小代价路径方法从计算机断层冠状动脉造影(CTCA)数据中提取冠状动脉中心线,并开发和评估一种新的方法来减少用户交互时间。

方法

评估了一种基于最小代价路径方法的半自动方法,该方法使用了两种不同的代价函数。第一种代价函数基于常用的血管性度量和强度信息,第二种是最近提出的基于区域统计的代价函数。用户交互被最小化到冠状动脉远端的一到两次鼠标点击。最小代价路径搜索的起点使用一种新开发的方法自动确定,该方法在其中一个轴位切片中找到主动脉中心的一个点。这一步确保了算法中所有计算密集的部分都可以预先计算。

结果

在 75 张图像中,主动脉定位程序的成功率达到了 100%。在 12 张图像的 48 个冠状动脉中,通过比较提取的中心线与手动标注的参考标准,定量评估了中心线提取的成功率和准确性。使用血管性/强度和区域统计代价函数,该方法分别能够正确提取 88%和 47%的血管中心线。对于仅近端血管,这些值分别为 97%和 86%。中心线提取的准确性,定义为自动提取中心线的正确部分与参考标准之间的平均距离,血管性/强度代价函数为 0.64mm,区域统计代价函数为 0.51mm。成功率测量的观察者间变异性为 99%,准确性测量的观察者间变异性为 0.42mm。使用表现最好的代价函数进行定性评估,在 63 张额外的 CTCA 图像中,252 个冠状动脉中的 233 个(92%)成功提取了中心线。

结论

结合最小的用户交互和低计算时间,所提出的结果表明,最小代价路径方法可以有效地作为临床实践和生物医学研究中后续分析的预处理步骤。

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