Dr. Shahab Ghafghazi Profile

Dr. Shahab Ghafghazi

at Univ of Louisville

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Proceedings Article | 15 March 2019 Paper

A comparative study of graph search algorithms for segmenting coronary arteries from cine angiography

Benjamin Veasey, Shahab Ghafghazi, Amir Amini

Proceedings Volume 10953, 109531T (2019) https://doi.org/10.1117/12.2511988

KEYWORDS: Image segmentation, Angiography, Arteries, Image processing algorithms and systems, Image filtering, 3D image processing, X-rays, X-ray imaging, Quantitative analysis

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Accurate and timely segmentation of coronary vessels in quantitative coronary angiography (QCA) may be important to ensure accurate patient diagnosis. This paper compares three variations of graph search algorithms for use in segmenting coronary arteries in X-ray angiographic images. For comparing these algorithms, we propose a semi-automatic vessel segmentation technique that combines Hessian-based filtering, Gabor filtering, and graph-based search routines for tracing the boundaries1,2. This allows for a more automated procedure by incorporating automatic centerline detection while the use of Gabor filtering promotes a more natural and geometrically continuous border segmentation1. The method requires minimal effort by the user; the only manual input required is a start and end-point along the vessel of interest. Three graph search methods were compared by analyzing the accuracy and computational speed of the segmentations while using each search technique: Dijkstra’s algorithm, a restricted Dijkstra’s algorithm, and the A* search algorithm were compared. The restricted Dijkstra’s and A* approaches reduced the computational time but resulted in low accuracies or outright segmentation failures. As outlined in the paper, Dijkstra’s algorithm results in a superior segmentation with only a marginal increase in computational time.

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