Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Identification of coronary artery stenosis based on hybrid segmentation and feature fusion Subject The topic of the resource Coronary artery disease; Keyframe extraction; stenosis; stenosis detection; X-ray angiography Description An account of the resource Coronary artery disease has been the utmost mutual heart disease in the past decades. Various research is going on to prevent this disease. Obstructive CAD occurs when one or more of the coronary arteries which supply blood to myocardium are narrowed owing to plaque build-up on the arteries inner walls, causing stenosis. The fundamental task required for the interpretation of coronary angiography is identification and quantification of severity of stenosis within the coronary circulation. Medical experts use X-ray coronary angiography to identify blood vessel/artery stenosis. Due to the artefact, the image has less clarity and it will be challenging for the medical expert to find the stenosis in the coronary artery. The solution to the problem a computational framework is proposed to segment the artery and spot the location of stenosis in the artery. Here the author presented an automatic method to detect stenosis from the X-ray angiogram image. A unified Computational method of Jerman, Level-set, fine-tuning the artery structure, is developed to extract the segmented artery features and detect the arterys stenosis. The current experimental outcomes illustrate that this computational method achieves average specificity, sensitivity, Accuracy, precision and F-scores of 95%, 97.5%, 98%, 97.5% and 97.5%, respectively. 2023 The Author(s). Published by Informa UK Limited, trading as Taylor &amp; Francis Group. Creator An entity primarily responsible for making the resource Kavipriya K.; Hiremath M. Source A related resource from which the described resource is derived Automatika, Vol-64, No. 3, pp. 622-633. Publisher An entity responsible for making the resource available Taylor and Francis Ltd. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1080/00051144.2023.2205727" target="_blank" rel="noreferrer noopener">https://doi.org/10.1080/00051144.2023.2205727</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158025936&amp;doi=10.1080%2F00051144.2023.2205727&amp;partnerID=40&amp;md5=c11d2756709585e2124c2f66717c98fb" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158025936&amp;doi=10.1080%2f00051144.2023.2205727&amp;partnerID=40&amp;md5=c11d2756709585e2124c2f66717c98fb</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Relation A related resource ISSN: 51144 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Kavipriya K., Department of Computer Science, Christ Deemed to be University, Bangalore, India; Hiremath M., Department of Computer Science, Christ Deemed to be University, Bangalore, India