Key result
Mathematical morphological operations demonstrated feasibility in achieving robust and consistently accurate segmentation of coronary arteries in X-ray angiogram images.
Mathematical morphological operations can provide robust and accurate automated segmentation of coronary arteries in X-ray angiograms.
Could aid consistent coronary analysis on angiograms; leaves open prospective clinical validation.
The medical imaging analysis is the process to view and understand the internal structure and function of the physiological system in medical diagnostic and therapeutic applications. Coronary artery angiography is playing a decisive role to determine the presence of cardiac diseases and the consequences for a therapeutic approach. So, the coronary angiography is remained for determining the extent, location and severity of the cardiac diseases. Automatically segmenting the coronary arteries in X-ray angiogram images has been an active area of research over the past several years and is an important task in medical imaging. Here mathematical morphological operations are used for segmenting the arteries. This method was implemented for a variety of clinical images. The results indicate the feasibility of achieving robust and consistently accurate image segmentation through this method.
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Arulmurugan et al. (2011) studied Coronary artery disease. Mathematical morphological operations for image segmentation was evaluated on Robust and consistently accurate image segmentation. Mathematical morphological operations demonstrated feasibility in achieving robust and consistently accurate segmentation of coronary arteries in X-ray angiogram images.
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