{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T17:46:19Z","timestamp":1770745579912,"version":"3.49.0"},"reference-count":40,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,6]],"date-time":"2021-08-06T00:00:00Z","timestamp":1628208000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["108-2321-B-415-003"],"award-info":[{"award-number":["108-2321-B-415-003"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["107-2221-E-415-007"],"award-info":[{"award-number":["107-2221-E-415-007"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Colonoscopies reduce the incidence of colorectal cancer through early recognition and resecting of the colon polyps. However, the colon polyp miss detection rate is as high as 26% in conventional colonoscopy. The search for methods to decrease the polyp miss rate is nowadays a paramount task. A number of algorithms or systems have been developed to enhance polyp detection, but few are suitable for real-time detection or classification due to their limited computational ability. Recent studies indicate that the automated colon polyp detection system is developing at an astonishing speed. Real-time detection with classification is still a yet to be explored field. Newer image pattern recognition algorithms with convolutional neuro-network (CNN) transfer learning has shed light on this topic. We proposed a study using real-time colonoscopies with the CNN transfer learning approach. Several multi-class classifiers were trained and mAP ranged from 38% to 49%. Based on an Inception v2 model, a detector adopting a Faster R-CNN was trained. The mAP of the detector was 77%, which was an improvement of 35% compared to the same type of multi-class classifier. Therefore, our results indicated that the polyp detection model could attain a high accuracy, but the polyp type classification still leaves room for improvement.<\/jats:p>","DOI":"10.3390\/s21165315","type":"journal-article","created":{"date-parts":[[2021,8,6]],"date-time":"2021-08-06T08:01:42Z","timestamp":1628236902000},"page":"5315","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Computer-Aided Colon Polyp Detection on High Resolution Colonoscopy Using Transfer Learning Techniques"],"prefix":"10.3390","volume":"21","author":[{"given":"Chia-Pei","family":"Tang","sequence":"first","affiliation":[{"name":"Division of Gastroenterology, Department of Internal Medicine, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Chiayi 62247, Taiwan"},{"name":"School of Medicine, Tzu Chi University, Hualien City 97004, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kai-Hong","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Management Information Systems, National Chiayi University, Chiayi 60054, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5008-7736","authenticated-orcid":false,"given":"Tu-Liang","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Management Information Systems, National Chiayi University, Chiayi 60054, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1977","DOI":"10.1056\/NEJM199312303292701","article-title":"Prevention of colorectal cancer by colonoscopic polypectomy","volume":"329","author":"Winawer","year":"1993","journal-title":"N. 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