{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,2]],"date-time":"2022-04-02T05:20:53Z","timestamp":1648876853507},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2021,12,22]],"date-time":"2021-12-22T00:00:00Z","timestamp":1640131200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,12,22]]},"abstract":"<jats:p>We propose a concise approach to facilitate the deep learning model for medical image classification of knee osteoarthritis severity. The characteristics of the input X-ray images are sharpened by a modified 5\u00d75 mask before training and testing in this work. We compare the inference accuracies of two experiments using the same architecture with images sharpened and not sharpened respectively. And we find it tangible that the former performs much better than the latter. This technique could also be helpful when applied onto the edge devices for object detection and image segmentation.<\/jats:p>","DOI":"10.3233\/faia210424","type":"book-chapter","created":{"date-parts":[[2021,12,29]],"date-time":"2021-12-29T10:29:38Z","timestamp":1640773778000},"source":"Crossref","is-referenced-by-count":0,"title":["Classification of Knee Osteoarthritis Severity Using Modified Masks to Preprocess X-ray Images in a Deep Learning Model"],"prefix":"10.3233","author":[{"given":"Ching-Chung","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Digital Media Design, Tatung Institute of Technology, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Proceedings of CECNet 2021"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA210424","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,29]],"date-time":"2021-12-29T10:29:39Z","timestamp":1640773779000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA210424"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,22]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia210424","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,22]]}}}