{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T08:47:20Z","timestamp":1771663640208,"version":"3.50.1"},"reference-count":24,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,10,25]],"date-time":"2021-10-25T00:00:00Z","timestamp":1635120000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF-2019K1A3A1A20093097"],"award-info":[{"award-number":["NRF-2019K1A3A1A20093097"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2019YFE0107800"],"award-info":[{"award-number":["2019YFE0107800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>One of the most common methods for diagnosing coronary artery disease is the use of the coronary artery calcium score CT. However, the current diagnostic method using the coronary artery calcium score CT requires a considerable time, because the radiologist must manually check the CT images one-by-one, and check the exact range. In this paper, three CNN models are applied for 1200 normal cardiovascular CT images, and 1200 CT images in which calcium is present in the cardiovascular system. We conduct the experimental test by classifying the CT image data into the original coronary artery calcium score CT images containing the entire rib cage, the cardiac segmented images that cut out only the heart region, and cardiac cropped images that are created by using the cardiac images that are segmented into nine sub-parts and enlarged. As a result of the experimental test to determine the presence of calcium in a given CT image using Inception Resnet v2, VGG, and Resnet 50 models, the highest accuracy of 98.52% was obtained when cardiac cropped image data was applied using the Resnet 50 model. Therefore, in this paper, it is expected that through further research, both the simple presence of calcium and the automation of the calcium analysis score for each coronary artery calcium score CT will become possible.<\/jats:p>","DOI":"10.3390\/s21217059","type":"journal-article","created":{"date-parts":[[2021,10,25]],"date-time":"2021-10-25T21:42:05Z","timestamp":1635198125000},"page":"7059","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Deep-Learning-Based Coronary Artery Calcium Detection from CT Image"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7865-7163","authenticated-orcid":false,"given":"Sungjin","family":"Lee","sequence":"first","affiliation":[{"name":"Department of Software Convergence, Soonchunhyang University, Asan 31538, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1232-0610","authenticated-orcid":false,"given":"Beanbonyka","family":"Rim","sequence":"additional","affiliation":[{"name":"Department of Software Convergence, Soonchunhyang University, Asan 31538, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sung-Shick","family":"Jou","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, Soonchunhyang University Cheonan Hospital, Cheonan 31151, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2550-2739","authenticated-orcid":false,"given":"Hyo-Wook","family":"Gil","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, Soonchunhyang University Cheonan Hospital, Cheonan 31151, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xibin","family":"Jia","sequence":"additional","affiliation":[{"name":"Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7467-3038","authenticated-orcid":false,"given":"Ahyoung","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Kennesaw State University, Marietta, GA 30144, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9963-5521","authenticated-orcid":false,"given":"Min","family":"Hong","sequence":"additional","affiliation":[{"name":"Department of Computer Software Engineering, Soonchunhyang University, Asan 31538, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,25]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2021, July 01). 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