{"id":"https://openalex.org/W2558168465","doi":"https://doi.org/10.1109/iceee.2016.7751228","title":"Thesholding methods review for the location of the Optic disc in retinal fundus color images","display_name":"Thesholding methods review for the location of the Optic disc in retinal fundus color images","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2558168465","doi":"https://doi.org/10.1109/iceee.2016.7751228","mag":"2558168465"},"language":"en","primary_location":{"id":"doi:10.1109/iceee.2016.7751228","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceee.2016.7751228","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 13th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)","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/A5061309293","display_name":"Laura J. Uribe-Valencia","orcid":null},"institutions":[{"id":"https://openalex.org/I39824353","display_name":"National Institute of Astrophysics, Optics and Electronics","ror":"https://ror.org/00bpmmc63","country_code":"MX","type":"facility","lineage":["https://openalex.org/I39824353"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Laura J. Uribe-Valencia","raw_affiliation_strings":["Electronics Department National Institute of Astrophysics, Optics, and Electronics Tonantzintla, Puebla, M\u00e9xico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics Department National Institute of Astrophysics, Optics, and Electronics Tonantzintla, Puebla, M\u00e9xico","institution_ids":["https://openalex.org/I39824353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010976827","display_name":"Jorge Mart\u00ednez\u2010Carballido","orcid":null},"institutions":[{"id":"https://openalex.org/I39824353","display_name":"National Institute of Astrophysics, Optics and Electronics","ror":"https://ror.org/00bpmmc63","country_code":"MX","type":"facility","lineage":["https://openalex.org/I39824353"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Jorge F. Martinez-Carballido","raw_affiliation_strings":["Electronics Department National Institute of Astrophysics, Optics, and Electronics Tonantzintla, Puebla, M\u00e9xico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics Department National Institute of Astrophysics, Optics, and Electronics Tonantzintla, Puebla, M\u00e9xico","institution_ids":["https://openalex.org/I39824353"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I39824353"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22503161,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"1","last_page":"6"},"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9879000186920166,"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/T10250","display_name":"Glaucoma and retinal disorders","score":0.9731000065803528,"subfield":{"id":"https://openalex.org/subfields/2731","display_name":"Ophthalmology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.8654336929321289},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7971658706665039},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6114909648895264},{"id":"https://openalex.org/keywords/optic-disc","display_name":"Optic disc","score":0.5968313217163086},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5612897276878357},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5550737380981445},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.5364805459976196},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5242310166358948},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5154284238815308},{"id":"https://openalex.org/keywords/adaptive-histogram-equalization","display_name":"Adaptive histogram equalization","score":0.4950503408908844},{"id":"https://openalex.org/keywords/fundus","display_name":"Fundus (uterus)","score":0.45293691754341125},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4405301511287689},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.41185152530670166},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.3482344150543213},{"id":"https://openalex.org/keywords/retinal","display_name":"Retinal","score":0.23998594284057617},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18171995878219604},{"id":"https://openalex.org/keywords/ophthalmology","display_name":"Ophthalmology","score":0.08500280976295471},{"id":"https://openalex.org/keywords/histogram-equalization","display_name":"Histogram equalization","score":0.07066687941551208},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.06042289733886719}],"concepts":[{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.8654336929321289},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7971658706665039},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6114909648895264},{"id":"https://openalex.org/C2779735895","wikidata":"https://www.wikidata.org/wiki/Q16873995","display_name":"Optic disc","level":3,"score":0.5968313217163086},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5612897276878357},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5550737380981445},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.5364805459976196},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5242310166358948},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5154284238815308},{"id":"https://openalex.org/C30387639","wikidata":"https://www.wikidata.org/wiki/Q4680744","display_name":"Adaptive histogram equalization","level":5,"score":0.4950503408908844},{"id":"https://openalex.org/C2776391266","wikidata":"https://www.wikidata.org/wiki/Q9612","display_name":"Fundus (uterus)","level":2,"score":0.45293691754341125},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4405301511287689},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.41185152530670166},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.3482344150543213},{"id":"https://openalex.org/C2780827179","wikidata":"https://www.wikidata.org/wiki/Q422001","display_name":"Retinal","level":2,"score":0.23998594284057617},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18171995878219604},{"id":"https://openalex.org/C118487528","wikidata":"https://www.wikidata.org/wiki/Q161437","display_name":"Ophthalmology","level":1,"score":0.08500280976295471},{"id":"https://openalex.org/C136943445","wikidata":"https://www.wikidata.org/wiki/Q1970240","display_name":"Histogram equalization","level":4,"score":0.07066687941551208},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.06042289733886719}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iceee.2016.7751228","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceee.2016.7751228","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 13th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"No poverty","score":0.75,"id":"https://metadata.un.org/sdg/1"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1615602451","https://openalex.org/W1978818813","https://openalex.org/W2011268029","https://openalex.org/W2016194585","https://openalex.org/W2057011351","https://openalex.org/W2079657870","https://openalex.org/W2080389430","https://openalex.org/W2083601800","https://openalex.org/W2083970667","https://openalex.org/W2108775640","https://openalex.org/W2120629405","https://openalex.org/W2142571901","https://openalex.org/W2170249894","https://openalex.org/W6680800823"],"related_works":["https://openalex.org/W2122667464","https://openalex.org/W2054831422","https://openalex.org/W2106731176","https://openalex.org/W2165297163","https://openalex.org/W2387104004","https://openalex.org/W2057981026","https://openalex.org/W3047671631","https://openalex.org/W1548186045","https://openalex.org/W2902098370","https://openalex.org/W2147223569"],"abstract_inverted_index":{"This":[0],"work":[1],"compares":[2],"Triangle,":[3],"Maximum":[4,193],"Entropy":[5,194],"and":[6,44,87,93,99,146,195,208],"Mean":[7,196],"Peak":[8],"thresholding":[9,61,75,132,166,187],"methods":[10],"to":[11,57,116,136],"locate":[12],"the":[13,21,59,65,71,74,107,118,123,140,142,147,175,181,205],"optic":[14,22],"disc":[15,23],"in":[16,28,106,204,211],"color":[17],"fundus":[18,108],"images.":[19,213],"Localizing":[20],"is":[24,36,114,134,172],"a":[25,127,161],"significant":[26],"task":[27],"an":[29],"automated":[30],"retinal":[31,45,53],"image":[32,68,109],"analysis":[33],"process":[34],"as":[35],"used":[37,56,115],"on":[38,70,84],"most":[39],"vessel":[40],"segmentation,":[41],"disease":[42],"diagnostic,":[43],"recognition":[46],"algorithms.":[47],"The":[48,168],"DIARETDBv1":[49],"dataset":[50],"includes":[51],"89":[52],"images":[54,80,101],"are":[55,81],"evaluate":[58],"3":[60],"methods.":[62,167],"To":[63],"analyze":[64,122],"effect":[66,124],"of":[67,73,79,125,139,155,177],"conditions":[69],"performance":[72,171],"methods,":[76],"three":[77],"set":[78],"created":[82],"based":[83],"their":[85],"contrast":[86],"quality:":[88],"high":[89],"contrast,":[90,92,112],"low":[91],"poor":[94],"quality;":[95],"with":[96,151,174,180,202],"58,":[97],"16,":[98],"15":[100],"respectively.":[102],"As":[103],"green":[104,144,149],"channel":[105,145,150],"provides":[110],"best":[111,206],"it":[113],"extract":[117],"Optic":[119],"disc.":[120],"We":[121],"applying":[126],"previous":[128],"preprocessing":[129,159],"technique,":[130],"each":[131],"method":[133,188],"applied":[135],"2":[137],"versions":[138],"image:":[141],"original":[143,148],"CLAHE.":[152],"In":[153],"terms":[154],"OD":[156,210],"location,":[157],"CLAHE":[158],"shows":[160],"great":[162],"improvement":[163],"for":[164],"all":[165,184],"average":[169],"Method":[170],"evaluated":[173],"percentage":[176],"intersected":[178],"pixels":[179],"groundtruth.":[182],"From":[183],"results":[185],"Triangle":[186],"performs":[189],"consistently":[190],"better":[191],"than":[192],"Peak,":[197],"achieving":[198],"70.78%":[199],"mean":[200],"overlap":[201],"groundtruth":[203],"case":[207],"locating":[209],"89/89":[212]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}