{"id":"https://openalex.org/W2922258838","doi":"https://doi.org/10.1117/12.2512239","title":"Fully-automated segmentation of optic disk from retinal images using deep learning techniques","display_name":"Fully-automated segmentation of optic disk from retinal images using deep learning techniques","publication_year":2019,"publication_date":"2019-03-13","ids":{"openalex":"https://openalex.org/W2922258838","doi":"https://doi.org/10.1117/12.2512239","mag":"2922258838"},"language":"en","primary_location":{"id":"doi:10.1117/12.2512239","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2512239","pdf_url":null,"source":{"id":"https://openalex.org/S4306519510","display_name":"Medical Imaging 2019: Computer-Aided Diagnosis","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2019: Computer-Aided Diagnosis","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014173669","display_name":"Fatemeh Zabihollahy","orcid":"https://orcid.org/0000-0003-3362-1009"},"institutions":[{"id":"https://openalex.org/I67031392","display_name":"Carleton University","ror":"https://ror.org/02qtvee93","country_code":"CA","type":"education","lineage":["https://openalex.org/I67031392"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Fatemeh Zabihollahy","raw_affiliation_strings":["Carleton Univ. (Canada)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carleton Univ. (Canada)","institution_ids":["https://openalex.org/I67031392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044454144","display_name":"Eranga Ukwatta","orcid":"https://orcid.org/0000-0003-0180-4716"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Eranga Ukwatta","raw_affiliation_strings":["Univ. of Guelph (Canada)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Guelph (Canada)","institution_ids":["https://openalex.org/I79817857"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1803,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.79047072,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"arXiv:1706.05350","issue":null,"first_page":"110","last_page":"110"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9679999947547913,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7018795013427734},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6256710886955261},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5969460606575012},{"id":"https://openalex.org/keywords/retinal","display_name":"Retinal","score":0.5647570490837097},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5278377532958984},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4736053943634033},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44828474521636963},{"id":"https://openalex.org/keywords/optic-disk","display_name":"Optic disk","score":0.4438026249408722},{"id":"https://openalex.org/keywords/ophthalmology","display_name":"Ophthalmology","score":0.1478603482246399},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.06796219944953918}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7018795013427734},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6256710886955261},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5969460606575012},{"id":"https://openalex.org/C2780827179","wikidata":"https://www.wikidata.org/wiki/Q422001","display_name":"Retinal","level":2,"score":0.5647570490837097},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5278377532958984},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4736053943634033},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44828474521636963},{"id":"https://openalex.org/C2983497740","wikidata":"https://www.wikidata.org/wiki/Q16873995","display_name":"Optic disk","level":3,"score":0.4438026249408722},{"id":"https://openalex.org/C118487528","wikidata":"https://www.wikidata.org/wiki/Q161437","display_name":"Ophthalmology","level":1,"score":0.1478603482246399},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.06796219944953918}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2512239","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2512239","pdf_url":null,"source":{"id":"https://openalex.org/S4306519510","display_name":"Medical Imaging 2019: Computer-Aided Diagnosis","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2019: Computer-Aided Diagnosis","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.5,"display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W1535703902","https://openalex.org/W1726196700","https://openalex.org/W1966375248","https://openalex.org/W1971654131","https://openalex.org/W2005312687","https://openalex.org/W2010868592","https://openalex.org/W2016194585","https://openalex.org/W2023422286","https://openalex.org/W2046288275","https://openalex.org/W2095705004","https://openalex.org/W2100805904","https://openalex.org/W2104095591","https://openalex.org/W2104324599","https://openalex.org/W2116040950","https://openalex.org/W2123215356","https://openalex.org/W2131910503","https://openalex.org/W2135914471","https://openalex.org/W2137015106","https://openalex.org/W2141460031","https://openalex.org/W2143516773","https://openalex.org/W2155806188","https://openalex.org/W2162698990","https://openalex.org/W2166460195","https://openalex.org/W2167917621","https://openalex.org/W2169551590","https://openalex.org/W2554946065","https://openalex.org/W2626017178","https://openalex.org/W4295245474","https://openalex.org/W6632241232","https://openalex.org/W6637529960","https://openalex.org/W6675770446"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W4387265590","https://openalex.org/W2611989081","https://openalex.org/W1995904975","https://openalex.org/W3032712071","https://openalex.org/W4389019322","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W1522196789","https://openalex.org/W2319016705"],"abstract_inverted_index":{"Segmentation":[0],"of":[1,15,27,35,42,58,63,82,142,159,163,167,175,181,252,259],"optic":[2],"disk":[3],"(OD)":[4],"from":[5,45,60,121,139,261],"retinal":[6,46,61,126,262],"images":[7,62,141,153],"is":[8,30,91],"a":[9,50,80,104,111],"crucial":[10],"task":[11],"for":[12,237,256],"early":[13,33],"detection":[14],"many":[16],"eye":[17,169],"diseases,":[18],"including":[19,179],"glaucoma":[20],"and":[21,68,97,165,183,187,192,210,229],"diabetic":[22,66,69,145],"retinopathy.":[23],"The":[24,89,128,246],"main":[25],"goal":[26],"this":[28],"research":[29],"to":[31,54,102,118,217,242],"facilitate":[32],"diagnosis":[34],"certain":[36],"pathologies":[37],"via":[38],"fully":[39],"automated":[40,257],"segmentation":[41,239,258],"the":[43,56,125,160,173,250],"OD":[44,59,78,120,164,238,260],"images.":[47,127,263],"We":[48,108],"propose":[49],"deep":[51],"learning-based":[52],"technique":[53],"delineate":[55],"boundary":[57],"patients":[64],"with":[65,154],"retinopathy":[67,146],"macular":[70],"edema.":[71],"In":[72],"our":[73,232,253],"method,":[74],"we":[75],"first":[76],"localized":[77],"within":[79],"region":[81],"interest":[83],"(ROI)":[84],"using":[85],"random":[86],"forest":[87],"(RF).":[88],"RF":[90],"an":[92],"ensemble":[93],"algorithm,":[94],"which":[95],"trains":[96],"combines":[98],"multiple":[99],"decision":[100],"trees":[101],"produce":[103],"highly":[105],"accurate":[106],"classifier.":[107],"then":[109],"used":[110],"convolutional":[112],"neural":[113],"network":[114],"(CNN)":[115],"based":[116],"model":[117],"segment":[119],"chosen":[122],"ROIs":[123],"in":[124,157,240],"developed":[129],"algorithm":[130],"has":[131],"been":[132],"validated":[133],"on":[134],"480,249":[135],"image":[136,147,230],"patches":[137],"extracted":[138],"49":[140],"public":[143],"Indian":[144],"dataset":[148,151],"(IDRiD).":[149],"This":[150],"includes":[152],"large":[155],"variability":[156],"terms":[158],"spatial":[161],"location":[162],"presence":[166],"other":[168,218],"lesions":[170],"that":[171],"resemble":[172],"contrast":[174],"OD.":[176],"Validation":[177],"metrics":[178],"average":[180],"Dice":[182],"Jaccard":[184],"indexes":[185],"(DI":[186],"JI),":[188],"Hausdorff":[189],"distance":[190],"(HD),":[191],"absolute":[193],"surface":[194],"difference":[195],"(ASD)":[196],"were":[197],"reported":[198],"as":[199,222],"82.62":[200],"\u00b1":[201,204,207,212],"11.07%,":[202],"71.78":[203],"14.87%,":[205],"13.19":[206],"10.90":[208],"mm,":[209],"22.74":[211],"19.78%,":[213],"respectively.":[214],"As":[215],"compared":[216],"alternative":[219],"methods,":[220],"such":[221],"K-nearest":[223],"neighbors":[224],"(KNN),":[225],"deformable":[226],"models,":[227],"graph-cuts,":[228],"thresholding,":[231],"method":[233,255],"yielded":[234],"higher":[235],"accuracy":[236],"comparison":[241],"manual":[243],"expert":[244],"delineation.":[245],"algorithm-generated":[247],"results":[248],"demonstrate":[249],"usefulness":[251],"proposed":[254]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
