{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T21:57:03Z","timestamp":1761429423601,"version":"3.41.2"},"reference-count":53,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,12,22]],"date-time":"2021-12-22T00:00:00Z","timestamp":1640131200000},"content-version":"vor","delay-in-days":355,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Computational Intelligence and Neuroscience"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>Optical coherence tomography (OCT) is a noninvasive imaging test. OCT imaging is analogous to ultrasound imaging, except that it uses light instead of sound. In this type of image, microscopic quality intratissue images are provided. In addition, fast and direct imaging of tissue morphology and reproducibility of results are the advantages of this imaging. Macular holes are a common eye disease that leads to visual impairment. The macular perforation is a rupture in the central part of the retina that, if left untreated, can lead to vision loss. A novel method for detecting macular holes using OCT images based on multilevel thresholding and derivation is proposed in this paper. This is a multistep method, which consists of segmentation, feature extraction, and feature selection. A combination of thresholding and derivation is used to diagnose the macular hole. After feature extraction, the features with useful information are selected and finally the output image of the macular hole is obtained. An open\u2010access data set of 200 images with the size of 224\u2009\u00d7\u2009224 pixels from Sankara Nethralaya (SN) Eye Hospital, Chennai, India, is used in the experiments. Experimental results show better\u2010diagnosing results than some recent diagnosing methods.<\/jats:p>","DOI":"10.1155\/2021\/6904217","type":"journal-article","created":{"date-parts":[[2021,12,22]],"date-time":"2021-12-22T17:50:10Z","timestamp":1640195410000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Macular Hole Detection Using a New Hybrid Method: Using Multilevel Thresholding and Derivation on Optical Coherence Tomographic Images"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5089-328X","authenticated-orcid":false,"given":"Sahand","family":"Shahalinejad","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6894-6802","authenticated-orcid":false,"given":"Reza","family":"Seifi Majdar","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,12,22]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.33969\/AIS.2019.11010"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.5301\/ejo.5000905"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2012.2184759"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2017.05.028"},{"key":"e_1_2_9_5_2","doi-asserted-by":"crossref","unstructured":"SlokomN. TrabelsiH. andZghalI. Segmentation of cyctoids macular edema in optical cohenrence tomography Proceedings of the 2016 2nd International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) March 2016 Monastir Tunisia 303\u2013306.","DOI":"10.1109\/ATSIP.2016.7523096"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1167\/iovs.06-1401"},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.1167\/iovs.09-5041"},{"key":"e_1_2_9_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcjo.2014.04.017"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2415-13-9"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.1136\/bjophthalmol-2015-307014"},{"key":"e_1_2_9_11_2","doi-asserted-by":"publisher","DOI":"10.2147\/OPTH.S96090"},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.1038\/eye.2016.42"},{"key":"e_1_2_9_13_2","doi-asserted-by":"publisher","DOI":"10.1038\/eye.2017.254"},{"key":"e_1_2_9_14_2","doi-asserted-by":"publisher","DOI":"10.1364\/oe.17.015659"},{"key":"e_1_2_9_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2018.07.258"},{"key":"e_1_2_9_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.01.023"},{"key":"e_1_2_9_17_2","doi-asserted-by":"publisher","DOI":"10.1364\/oe.23.024699"},{"key":"e_1_2_9_18_2","doi-asserted-by":"publisher","DOI":"10.1088\/1612-202x\/aa7b96"},{"key":"e_1_2_9_19_2","doi-asserted-by":"publisher","DOI":"10.1117\/1.429925"},{"key":"e_1_2_9_20_2","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2009.2038375"},{"key":"e_1_2_9_21_2","doi-asserted-by":"publisher","DOI":"10.1364\/ol.38.001280"},{"key":"e_1_2_9_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.07.004"},{"key":"e_1_2_9_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2019.04.033"},{"key":"e_1_2_9_24_2","doi-asserted-by":"publisher","DOI":"10.1088\/1612-202x\/aaaeb0"},{"key":"e_1_2_9_25_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ophtha.2005.10.005"},{"key":"e_1_2_9_26_2","doi-asserted-by":"publisher","DOI":"10.1136\/bjo.2007.128447"},{"key":"e_1_2_9_27_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.07.079"},{"key":"e_1_2_9_28_2","doi-asserted-by":"crossref","unstructured":"GirishG. N. KothariA. R. andRajanJ. Automated segmentation of intra-retinal cysts from optical coherence tomography scans using marker controlled watershed transform Proceedings of the 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) August 2016 Florida USA IEEE 1292\u20131295 https:\/\/doi.org\/10.1109\/embc.2016.7590943 2-s2.0-85009115061.","DOI":"10.1109\/EMBC.2016.7590943"},{"key":"e_1_2_9_29_2","doi-asserted-by":"publisher","DOI":"10.1109\/jbhi.2017.2675382"},{"key":"e_1_2_9_30_2","doi-asserted-by":"publisher","DOI":"10.1364\/OPEX.13.010200"},{"key":"e_1_2_9_31_2","doi-asserted-by":"publisher","DOI":"10.1364\/boe.2.001743"},{"key":"e_1_2_9_32_2","article-title":"Two stage contour evolution for automatic segmentation of choroid and cornea in OCT images","volume":"36","author":"George N.","year":"2019","journal-title":"Biocybernetics and Biomedical Engineering"},{"key":"e_1_2_9_33_2","article-title":"IT-supported skill-mix change and standardisation in integrated eyecare: lessons from two screening projects in The Netherlands","volume":"7","author":"Berg M.","year":"2007","journal-title":"International Journal of Integrated Care"},{"key":"e_1_2_9_34_2","doi-asserted-by":"publisher","DOI":"10.1117\/12.921299"},{"key":"e_1_2_9_35_2","doi-asserted-by":"publisher","DOI":"10.1118\/1.4816310"},{"key":"e_1_2_9_36_2","doi-asserted-by":"publisher","DOI":"10.1049\/iet-ipr.2018.5396"},{"key":"e_1_2_9_37_2","doi-asserted-by":"publisher","DOI":"10.1111\/aos.13665"},{"key":"e_1_2_9_38_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.heliyon.2019.e01271"},{"key":"e_1_2_9_39_2","doi-asserted-by":"crossref","unstructured":"StankiewiczA. MarciniakT. AdamD. StopaM. RakowiczP. andMarciniakE. Novel full-automatic approach for segmentation of epiretinal membrane from 3D OCT images Proceedings of the 2017 Signal Processing: Algorithms Architectures Arrangements and Applications (SPA) September 2017 Poznan Poland IEEE 100\u2013105 https:\/\/doi.org\/10.23919\/spa.2017.8166846 2-s2.0-85041547430.","DOI":"10.23919\/SPA.2017.8166846"},{"key":"e_1_2_9_40_2","doi-asserted-by":"publisher","DOI":"10.1117\/1.jbo.21.7.076015"},{"key":"e_1_2_9_41_2","doi-asserted-by":"crossref","unstructured":"AthiraS. C. RoyR. M. andAneeshR. P. Computerized detection of macular edema using OCT images based on fractal texture analysis Proceedings of the 2018 International CET Conference on Control Communication and Computing (IC4) July 2018 Thiruvananthapuram India IEEE 326\u2013330 https:\/\/doi.org\/10.1109\/cetic4.2018.8530952 2-s2.0-85058217526.","DOI":"10.1109\/CETIC4.2018.8530952"},{"key":"e_1_2_9_42_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2767908"},{"key":"e_1_2_9_43_2","doi-asserted-by":"publisher","DOI":"10.1109\/lsp.2019.2917779"},{"key":"e_1_2_9_44_2","doi-asserted-by":"publisher","DOI":"10.1117\/1.jbo.22.6.066014"},{"key":"e_1_2_9_45_2","doi-asserted-by":"crossref","unstructured":"El TanbolyA. IsmailM. SwitalaA. MahmoudM. AhmedS. NeyerT. PalacioA. HadayerA. El-AzabM. SchaalS. andEl-BazA. A novel automatic segmentation of healthy and diseased retinal layers from OCT scans Proceedings of the 2016 IEEE International Conference on Image Processing (ICIP) September 2016 Phoenix AZ USA IEEE 116\u2013120 https:\/\/doi.org\/10.1109\/icip.2016.7532330 2-s2.0-85006753242.","DOI":"10.1109\/ICIP.2016.7532330"},{"key":"e_1_2_9_46_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2016.06.007"},{"key":"e_1_2_9_47_2","doi-asserted-by":"publisher","DOI":"10.1038\/eye.2015.262"},{"key":"e_1_2_9_48_2","doi-asserted-by":"publisher","DOI":"10.2147\/opth.s224279"},{"key":"e_1_2_9_49_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2011.06.005"},{"key":"e_1_2_9_50_2","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/794574"},{"key":"e_1_2_9_51_2","first-page":"443","article-title":"Optimal multilevel image thresholding: an analysis with PSO and BFO algorithms","volume":"8","author":"Aust J.","year":"2014","journal-title":"Basic and Applied Science"},{"key":"e_1_2_9_52_2","first-page":"51","article-title":"Chaotic cuckoo search and Kapur\/Tsallis approach in segmentation of t.cruzi from blood smear images","volume":"14","author":"Lakshmi V. S.","year":"2016","journal-title":"International Journal of Computer Science and Information Security"},{"key":"e_1_2_9_53_2","doi-asserted-by":"publisher","DOI":"10.1364\/oe.20.001337"}],"container-title":["Computational Intelligence and Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2021\/6904217.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2021\/6904217.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/2021\/6904217","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T12:07:42Z","timestamp":1722946062000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/2021\/6904217"}},"subtitle":[],"editor":[{"given":"V.","family":"Rajinikanth","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":53,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["10.1155\/2021\/6904217"],"URL":"https:\/\/doi.org\/10.1155\/2021\/6904217","archive":["Portico"],"relation":{},"ISSN":["1687-5265","1687-5273"],"issn-type":[{"type":"print","value":"1687-5265"},{"type":"electronic","value":"1687-5273"}],"subject":[],"published":{"date-parts":[[2021,1]]},"assertion":[{"value":"2021-07-15","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-11-24","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-12-22","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"6904217"}}