Advanced Computational Method to Extract Heart Artery Region

Advanced Computational Method to Extract Heart Artery Region

© 2022 by IJETT Journal
Volume-70 Issue-6
Year of Publication : 2022
Authors : K. Kavipriya, Manjunatha Hiremath
DOI : 10.14445/22315381/IJETT-V70I6P237

How to Cite?

K. Kavipriya, Manjunatha Hiremath, "Advanced Computational Method to Extract Heart Artery Region," International Journal of Engineering Trends and Technology, vol. 70, no. 6, pp. 366-378, 2022. Crossref,

Coronary artery disease, also known as coronary heart disease, is the thinning or blockage of heart arteries, which is generally caused utilizing the build-up of fatty material called plaque. The coronary angiogram test is currently the most utilized method for identifying the stenosis status of arteries in the heart. The objective of the proposed hybrid segmentation method is to extract the artery region of the heart from angiogram imagery. Numerous angiogram video clips have been considered in the dataset in this research work. These video clips were acquired from a healthcare center with the due consent of patients and the concerned healthcare personnel. Most angiogram videos consist of unclear images, or the contents are generally not clear, and medical experts fail to acquire accurate information about the damages or blocks formed in arteries due to the same reason. A hybrid computational method to extract well-defined images of heart arteries using Frangi and motion blur features from angiogram imagery has been proposed to address this issue. Fifty patients' information has been used as the dataset for experimentation purposes in this research work. The enhanced Frangi filter is used on the dataset to obtain edge information to enhance the input image based on the Hessian matrix. Further, the motion blur helps in automatically tracking/tracing the pixel direction using the optical flow method. In this method, the complete structure of the artery is extracted. The results, when compared to the existing methods, have proven to be novel and more optimal.

Coronary Angiogram, Artery, Stenosis, Segmentation, Frangi Filter, Motion Blur.

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