{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T21:07:08Z","timestamp":1790629628418,"version":"4.1.0"},"reference-count":31,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,12,17]],"date-time":"2022-12-17T00:00:00Z","timestamp":1671235200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Wan Azani Mustafa"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>A corneal ulcers are one of the most common eye diseases. They come from various infections, such as bacteria, viruses, or parasites. They may lead to ocular morbidity and visual disability. Therefore, early detection can reduce the probability of reaching the visually impaired. One of the most common techniques exploited for corneal ulcer screening is slit-lamp images. This paper proposes two highly accurate automated systems to localize the corneal ulcer region. The designed approaches are image processing techniques with Hough transform and deep learning approaches. The two methods are validated and tested on the publicly available SUSTech-SYSU database. The accuracy is evaluated and compared between both systems. Both systems achieve an accuracy of more than 90%. However, the deep learning approach is more accurate than the traditional image processing techniques. It reaches 98.9% accuracy and Dice similarity 99.3%. However, the first method does not require parameters to optimize an explicit training model. The two approaches can perform well in the medical field. Moreover, the first model has more leverage than the deep learning model because the last one needs a large training dataset to build reliable software in clinics. Both proposed methods help physicians in corneal ulcer level assessment and improve treatment efficiency.<\/jats:p>","DOI":"10.3390\/diagnostics12123204","type":"journal-article","created":{"date-parts":[[2022,12,19]],"date-time":"2022-12-19T06:58:29Z","timestamp":1671433109000},"page":"3204","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Automated Detection of Corneal Ulcer Using Combination Image Processing and Deep Learning"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5587-3974","authenticated-orcid":false,"given":"Isam Abu","family":"Qasmieh","sequence":"first","affiliation":[{"name":"Biomedical Systems and Medical Informatics Engineering, Yarmouk University, Irbid 21163, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2966-6442","authenticated-orcid":false,"given":"Hiam","family":"Alquran","sequence":"additional","affiliation":[{"name":"Biomedical Systems and Medical Informatics Engineering, Yarmouk University, Irbid 21163, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ala\u2019a","family":"Zyout","sequence":"additional","affiliation":[{"name":"Biomedical Systems and Medical Informatics Engineering, Yarmouk University, Irbid 21163, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7747-1183","authenticated-orcid":false,"given":"Yazan","family":"Al-Issa","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Yarmouk University, Irbid 21163, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7260-6085","authenticated-orcid":false,"given":"Wan Azani","family":"Mustafa","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering & Technology, Campus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Arau, Perlis 02600, Malaysia"},{"name":"Advanced Computing (AdvComp), Centre of Excellence (CoE), Campus Pauh Putra, Universiti Malaysia Perlis (UniMAP), Arau, Perlis 02600, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5450-3311","authenticated-orcid":false,"given":"Mohammed","family":"Alsalatie","sequence":"additional","affiliation":[{"name":"The Institute of Biomedical Technology, King Hussein Medical Center, Royal Jordanian Medical Service, Amman 11855, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"100856","DOI":"10.1016\/j.ajoc.2020.100856","article-title":"A corneal ring ulcer","volume":"20","author":"Alhajraf","year":"2020","journal-title":"Am. 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