Optimized adaptive frangi-based coronary artery segmentation using genetic algorithm

Abstract EN

Coronary arteries’ diseases are deliberated as one of the most common heart diseases leading to death worldwide.

for their early detection, the x-ray angiography is uses as a benchmark imaging modality for diagnosis.

the acquired x-ray angiography images usually suffer from low quality, and the presence of noise.

therefore, for developing a computer-aided diagnosis (CAD) system, vessel enhancement and segmentation play significant role.

in this paper, an optimized adapted filter based on Frangi filter was proposed for superior segmentation of the angiography images using genetic algorithm (GA).

the original angiography images were initially preprocessed to enhance their contrast followed by generating the vesselness map using the proposed optimized Frangi filter.

then, a segmentation technique was applied to extract only the main artery vessel.

the experimental results on angiography images established the superiority of the vessel regions extraction showing 98.58% accuracy compared to the state-of-the-art.