{"id":"https://openalex.org/W4205477102","doi":"https://doi.org/10.1109/bibm52615.2021.9669581","title":"A New Method Based on Deep Learning to Detect Lesions in Retinal Images using YOLOv5","display_name":"A New Method Based on Deep Learning to Detect Lesions in Retinal Images using YOLOv5","publication_year":2021,"publication_date":"2021-12-09","ids":{"openalex":"https://openalex.org/W4205477102","doi":"https://doi.org/10.1109/bibm52615.2021.9669581"},"language":"en","primary_location":{"id":"doi:10.1109/bibm52615.2021.9669581","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm52615.2021.9669581","pdf_url":null,"source":{"id":"https://openalex.org/S4363607735","display_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"article","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/A5113953329","display_name":"Carlos Silva","orcid":"https://orcid.org/0000-0001-8362-8984"},"institutions":[{"id":"https://openalex.org/I169248161","display_name":"Universidade Federal de Pelotas","ror":"https://ror.org/05msy9z54","country_code":"BR","type":"education","lineage":["https://openalex.org/I169248161"]},{"id":"https://openalex.org/I4210147797","display_name":"Instituto Federal Farroupilha","ror":"https://ror.org/04eq71r04","country_code":"BR","type":"education","lineage":["https://openalex.org/I4210147797"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Carlos Santos","raw_affiliation_strings":["Federal Institute of Education, Science and Technology Farroupilha, Alegrete, Brazil","Postgraduate Program in Computing (PPGC), Federal University of Pelotas, Pelotas, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal Institute of Education, Science and Technology Farroupilha, Alegrete, Brazil","institution_ids":["https://openalex.org/I4210147797"]},{"raw_affiliation_string":"Postgraduate Program in Computing (PPGC), Federal University of Pelotas, Pelotas, Brazil","institution_ids":["https://openalex.org/I169248161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075071243","display_name":"Mar\u00edlton Sanchotene de Aguiar","orcid":"https://orcid.org/0000-0002-5247-6022"},"institutions":[{"id":"https://openalex.org/I169248161","display_name":"Universidade Federal de Pelotas","ror":"https://ror.org/05msy9z54","country_code":"BR","type":"education","lineage":["https://openalex.org/I169248161"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Marilton Aguiar","raw_affiliation_strings":["Postgraduate Program in Computing (PPGC), Federal University of Pelotas, Pelotas, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Postgraduate Program in Computing (PPGC), Federal University of Pelotas, Pelotas, Brazil","institution_ids":["https://openalex.org/I169248161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027750704","display_name":"Daniel Welfer","orcid":"https://orcid.org/0000-0003-1560-423X"},"institutions":[{"id":"https://openalex.org/I33501960","display_name":"Universidade Federal de Santa Maria","ror":"https://ror.org/01b78mz79","country_code":"BR","type":"education","lineage":["https://openalex.org/I33501960"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Daniel Welfer","raw_affiliation_strings":["Departament of Applied Computing, Federal University of Santa Maria, Santa Maria, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departament of Applied Computing, Federal University of Santa Maria, Santa Maria, Brazil","institution_ids":["https://openalex.org/I33501960"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033694850","display_name":"Bruno Belloni","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bruno Belloni","raw_affiliation_strings":["Federal Institute of Education, Science and Technology Sul-Rio-Grandense, Passo Fundo, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal Institute of Education, Science and Technology Sul-Rio-Grandense, Passo Fundo, Brazil","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5113953329"],"corresponding_institution_ids":["https://openalex.org/I169248161","https://openalex.org/I4210147797"],"apc_list":null,"apc_paid":null,"fwci":0.9099,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.70490566,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3513","last_page":"3520"},"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/T12599","display_name":"Retinal and Optic Conditions","score":0.998199999332428,"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"}},{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9941999912261963,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7388957738876343},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7016302347183228},{"id":"https://openalex.org/keywords/fundus","display_name":"Fundus (uterus)","score":0.6878597736358643},{"id":"https://openalex.org/keywords/diabetic-retinopathy","display_name":"Diabetic retinopathy","score":0.6761061549186707},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6156201362609863},{"id":"https://openalex.org/keywords/retinal","display_name":"Retinal","score":0.5573272705078125},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5382129549980164},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49797940254211426},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49597224593162537},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47953104972839355},{"id":"https://openalex.org/keywords/retinopathy","display_name":"Retinopathy","score":0.46151942014694214},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4439460039138794},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3372229337692261},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32532376050949097},{"id":"https://openalex.org/keywords/ophthalmology","display_name":"Ophthalmology","score":0.2550027370452881},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2026539146900177},{"id":"https://openalex.org/keywords/diabetes-mellitus","display_name":"Diabetes mellitus","score":0.08210337162017822}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7388957738876343},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7016302347183228},{"id":"https://openalex.org/C2776391266","wikidata":"https://www.wikidata.org/wiki/Q9612","display_name":"Fundus (uterus)","level":2,"score":0.6878597736358643},{"id":"https://openalex.org/C2779829184","wikidata":"https://www.wikidata.org/wiki/Q631361","display_name":"Diabetic retinopathy","level":3,"score":0.6761061549186707},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6156201362609863},{"id":"https://openalex.org/C2780827179","wikidata":"https://www.wikidata.org/wiki/Q422001","display_name":"Retinal","level":2,"score":0.5573272705078125},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5382129549980164},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49797940254211426},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49597224593162537},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47953104972839355},{"id":"https://openalex.org/C2778313320","wikidata":"https://www.wikidata.org/wiki/Q550455","display_name":"Retinopathy","level":3,"score":0.46151942014694214},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4439460039138794},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3372229337692261},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32532376050949097},{"id":"https://openalex.org/C118487528","wikidata":"https://www.wikidata.org/wiki/Q161437","display_name":"Ophthalmology","level":1,"score":0.2550027370452881},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2026539146900177},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.08210337162017822},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm52615.2021.9669581","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm52615.2021.9669581","pdf_url":null,"source":{"id":"https://openalex.org/S4363607735","display_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1921523184","https://openalex.org/W2162698990","https://openalex.org/W2523246573","https://openalex.org/W2765407302","https://openalex.org/W2948685905","https://openalex.org/W2962766617","https://openalex.org/W2963446712","https://openalex.org/W2963857746","https://openalex.org/W2971900262","https://openalex.org/W2977650145","https://openalex.org/W3005762692","https://openalex.org/W3015209252","https://openalex.org/W3018757597","https://openalex.org/W3034971973","https://openalex.org/W3038091703","https://openalex.org/W3042011474","https://openalex.org/W3097127971","https://openalex.org/W3106250896","https://openalex.org/W3112139896","https://openalex.org/W3157490352","https://openalex.org/W3184439416","https://openalex.org/W3200676841","https://openalex.org/W4293584584","https://openalex.org/W6639102338","https://openalex.org/W6640185926","https://openalex.org/W6727249380","https://openalex.org/W6745136726","https://openalex.org/W6750227808","https://openalex.org/W6777046832","https://openalex.org/W6798838024"],"related_works":["https://openalex.org/W1980571360","https://openalex.org/W3176448898","https://openalex.org/W4379115808","https://openalex.org/W3207986206","https://openalex.org/W2429379476","https://openalex.org/W1979866946","https://openalex.org/W2584074590","https://openalex.org/W4226141369","https://openalex.org/W2413307231","https://openalex.org/W4361800274"],"abstract_inverted_index":{"Diabetic":[0,109],"Retinopathy":[1,110],"is":[2],"one":[3],"of":[4,8,32,42,49,53,60,96,127,134],"the":[5,39,43,47,57,93,107,116,120,140,147,151,162],"leading":[6],"causes":[7],"vision":[9],"loss":[10],"and":[11,23,25,45,82,104,112,119,129,136],"presents":[12],"in":[13,38,92,139,146,161],"its":[14],"initial":[15],"phase":[16],"retinal":[17],"lesions,":[18,54],"such":[19],"as":[20],"microaneurysms,":[21],"hemorrhages,":[22],"hard":[24],"soft":[26],"exudates.":[27],"Therefore,":[28],"computational":[29],"models":[30,72],"capable":[31],"detecting":[33],"these":[34],"lesions":[35],"can":[36],"help":[37],"early":[40],"diagnosis":[41,95],"disease":[44],"prevent":[46],"manifestation":[48],"more":[50],"severe":[51],"forms":[52],"helping":[55],"define":[56],"best":[58],"form":[59],"treatment.":[61],"This":[62],"work":[63],"proposes":[64],"a":[65,88],"method":[66,153],"based":[67,114],"on":[68,115],"deep":[69],"neural":[70],"network":[71],"that":[73,90,150],"perform":[74],"one-stage":[75],"object":[76],"detection,":[77],"using":[78,106],"state-of-the-art":[79],"data":[80],"augmentation":[81],"transfer":[83],"learning":[84],"techniques":[85],"to":[86,157],"present":[87],"model":[89,100],"aids":[91],"medical":[94],"fundus":[97],"lesions.":[98],"The":[99,143],"was":[101],"trained,":[102],"adjusted,":[103],"evaluated":[105],"DDR":[108],"Dataset,":[111],"implemented":[113],"YOLOv5":[117],"architecture":[118],"PyTorch":[121],"framework,":[122],"achieving":[123],"values":[124],"for":[125,131],"mAP":[126],"0.1040":[128],"0.0283":[130],"IoU":[132],"threshold":[133],"0.5":[135],"0.5:0.95":[137],"respectively,":[138],"validation":[141],"set.":[142],"results":[144,156],"obtained":[145],"experiments":[148],"demonstrate":[149],"proposed":[152],"presented":[154],"superior":[155],"equivalent":[158],"works":[159],"found":[160],"literature.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-29T09:16:38.111599","created_date":"2025-10-10T00:00:00"}
