{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T16:29:37Z","timestamp":1780504177897,"version":"3.54.1"},"reference-count":51,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2021,9,7]],"date-time":"2021-09-07T00:00:00Z","timestamp":1630972800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Colonoscopy screening and colonoscopic polypectomy can decrease the incidence and mortality rate of colorectal cancer (CRC). The adenoma detection rate and accuracy of diagnosis of colorectal polyp which vary in different experienced endoscopists have impact on the colonoscopy protection effect of CRC. The work proposed a colorectal polyp image detection and classification system through grayscale images and deep learning. The system collected the data of CVC-Clinic and 1000 colorectal polyp images of Linkou Chang Gung Medical Hospital. The red-green-blue (RGB) images were transformed to 0 to 255 grayscale images. Polyp detection and classification were performed by convolutional neural network (CNN) model. Data for polyp detection was divided into five groups and tested by 5-fold validation. The accuracy of polyp detection was 95.1% for grayscale images which is higher than 94.1% for RGB and narrow-band images. The diagnostic accuracy, precision and recall rates were 82.8%, 82.5% and 95.2% for narrow-band images, respectively. The experimental results show that grayscale images achieve an equivalent or even higher accuracy of polyp detection than RGB images for lightweight computation. It is also found that the accuracy of polyp detection and classification is dramatically decrease when the size of polyp images small than 1600 pixels. It is recommended that clinicians could adjust the distance between the lens and polyps appropriately to enhance the system performance when conducting computer-assisted colorectal polyp analysis.<\/jats:p>","DOI":"10.3390\/s21185995","type":"journal-article","created":{"date-parts":[[2021,9,8]],"date-time":"2021-09-08T02:41:07Z","timestamp":1631068867000},"page":"5995","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":46,"title":["Colorectal Polyp Image Detection and Classification through Grayscale Images and Deep Learning"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5838-8886","authenticated-orcid":false,"given":"Chen-Ming","family":"Hsu","sequence":"first","affiliation":[{"name":"Department of Gastroenterology and Hepatology, Linkou Chang Gung Memorial Hospital and Chang Gung University College of Medicine, No. 5, Fuxing St., Guishan Dist., Taoyuan City 333, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1714-9122","authenticated-orcid":false,"given":"Chien-Chang","family":"Hsu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, Fu-Jen Catholic University, 510 Chung Cheng Rd., Hsinchuang Dist., New Taipei City 242, Taiwan"},{"name":"Graduate Institute of Applied Science and Engineering, Fu-Jen Catholic University, 510 Chung Cheng Rd., Hsinchuang Dist., New Taipei City 242, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhe-Ming","family":"Hsu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, Fu-Jen Catholic University, 510 Chung Cheng Rd., Hsinchuang Dist., New Taipei City 242, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng-Yu","family":"Shih","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, Fu-Jen Catholic University, 510 Chung Cheng Rd., Hsinchuang Dist., New Taipei City 242, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meng-Lin","family":"Chang","sequence":"additional","affiliation":[{"name":"Graduate Institute of Applied Science and Engineering, Fu-Jen Catholic University, 510 Chung Cheng Rd., Hsinchuang Dist., New Taipei City 242, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tsung-Hsing","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology and Hepatology, Linkou Chang Gung Memorial Hospital and Chang Gung University College of Medicine, No. 5, Fuxing St., Guishan Dist., Taoyuan City 333, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"209","DOI":"10.3322\/caac.21660","article-title":"Global Cancer Statistics 2020: GLO-BOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries","volume":"71","author":"Sung","year":"2021","journal-title":"CA Cancer J. 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