{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T05:38:54Z","timestamp":1775713134047,"version":"3.50.1"},"reference-count":12,"publisher":"Wiley","license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["129619"],"award-info":[{"award-number":["129619"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["International Journal of Biomedical Imaging"],"published-print":{"date-parts":[[2017]]},"abstract":"<jats:p>Horizontal and vertical cup to disc ratios are the most crucial parameters used clinically to detect glaucoma or monitor its progress and are manually evaluated from retinal fundus images of the optic nerve head. Due to the rarity of the glaucoma experts as well as the increasing in glaucoma\u2019s population, an automatically calculated horizontal and vertical cup to disc ratios (HCDR and VCDR, resp.) can be useful for glaucoma screening. We report on two algorithms to calculate the HCDR and VCDR. In the algorithms, level set and inpainting techniques were developed for segmenting the disc, while thresholding using Type-II fuzzy approach was developed for segmenting the cup. The results from the algorithms were verified using the manual markings of images from a dataset of glaucomatous images (retinal fundus images for glaucoma analysis (RIGA dataset)) by six ophthalmologists. The algorithm\u2019s accuracy for HCDR and VCDR combined was 74.2%. Only the accuracy of manual markings by one ophthalmologist was higher than the algorithm\u2019s accuracy. The algorithm\u2019s best agreement was with markings by ophthalmologist number 1 in 230 images (41.8%) of the total tested images.<\/jats:p>","DOI":"10.1155\/2017\/4826385","type":"journal-article","created":{"date-parts":[[2017,8,29]],"date-time":"2017-08-29T17:01:39Z","timestamp":1504026099000},"page":"1-19","source":"Crossref","is-referenced-by-count":20,"title":["An Automatic Image Processing System for Glaucoma Screening"],"prefix":"10.1155","volume":"2017","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0076-6204","authenticated-orcid":true,"given":"Ahmed","family":"Almazroa","sequence":"first","affiliation":[{"name":"Kellogg Eye Center, University of Michigan, 1000 Wall St, Ann Arbor, MI 48105, USA"},{"name":"King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, National Guard, Riyadh 14611, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sami","family":"Alodhayb","sequence":"additional","affiliation":[{"name":"Bin Rushed Ophthalmic Center, King Fahd Branch Rd, Opposite King Fahad National Library, Al Olaya, Riyadh 12311, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9835-7897","authenticated-orcid":true,"given":"Kaamran","family":"Raahemifar","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Ryerson University, 350 Victoria St., Toronto, ON, Canada M5B 2K3"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vasudevan","family":"Lakshminarayanan","sequence":"additional","affiliation":[{"name":"School of Optometry and Vision Science, University of Waterloo, 200 Columbia St. W., Waterloo, ON, Canada N2L 3G1"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"15","year":"1990"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2013.2247770"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-68240-0_2"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1136\/bjo.82.10.1118"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1155\/2015\/180972"},{"issue":"7","key":"8","doi-asserted-by":"crossref","first-page":"5209","DOI":"10.15680\/IJIRSET.2015.0407024","volume":"4","year":"2015","journal-title":"Int J Innov Res Sci Eng Technol"},{"key":"10","year":"2014"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24888-2_17"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.2147\/OPTH.S117157"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.5566\/ias.1155"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1007\/s10792-016-0329-x"},{"key":"6","first-page":"327","volume-title":"Automated detection of optic disc in glaucoma","year":"2015"}],"container-title":["International Journal of Biomedical Imaging"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/ijbi\/2017\/4826385.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/ijbi\/2017\/4826385.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/ijbi\/2017\/4826385.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,8,29]],"date-time":"2017-08-29T17:01:42Z","timestamp":1504026102000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/ijbi\/2017\/4826385\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"references-count":12,"alternative-id":["4826385","4826385"],"URL":"https:\/\/doi.org\/10.1155\/2017\/4826385","relation":{},"ISSN":["1687-4188","1687-4196"],"issn-type":[{"value":"1687-4188","type":"print"},{"value":"1687-4196","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017]]}}}