{"id":"https://openalex.org/W3006026428","doi":"https://doi.org/10.1109/access.2020.2974027","title":"Attention Guided U-Net With Atrous Convolution for Accurate Retinal Vessels Segmentation","display_name":"Attention Guided U-Net With Atrous Convolution for Accurate Retinal Vessels Segmentation","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3006026428","doi":"https://doi.org/10.1109/access.2020.2974027","mag":"3006026428"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2974027","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2974027","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08999616.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08999616.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110638237","display_name":"Yan Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I55022517","display_name":"Heilongjiang University","ror":"https://ror.org/04zyhq975","country_code":"CN","type":"education","lineage":["https://openalex.org/I55022517"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yan Lv","raw_affiliation_strings":["College of Electronic Engineering, Heilongjiang University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Engineering, Heilongjiang University, Harbin, China","institution_ids":["https://openalex.org/I55022517"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079274590","display_name":"Hui Ma","orcid":"https://orcid.org/0000-0002-0513-2462"},"institutions":[{"id":"https://openalex.org/I55022517","display_name":"Heilongjiang University","ror":"https://ror.org/04zyhq975","country_code":"CN","type":"education","lineage":["https://openalex.org/I55022517"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Ma","raw_affiliation_strings":["College of Electronic Engineering, Heilongjiang University, Harbin, China","Key Laboratory of Information Fusion Estimation and Detection, Heilongjiang University, Harbin, China"],"raw_orcid":"https://orcid.org/0000-0002-0513-2462","affiliations":[{"raw_affiliation_string":"College of Electronic Engineering, Heilongjiang University, Harbin, China","institution_ids":["https://openalex.org/I55022517"]},{"raw_affiliation_string":"Key Laboratory of Information Fusion Estimation and Detection, Heilongjiang University, Harbin, China","institution_ids":["https://openalex.org/I55022517"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063088587","display_name":"Jianian Li","orcid":"https://orcid.org/0000-0002-5407-3956"},"institutions":[{"id":"https://openalex.org/I55022517","display_name":"Heilongjiang University","ror":"https://ror.org/04zyhq975","country_code":"CN","type":"education","lineage":["https://openalex.org/I55022517"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianian Li","raw_affiliation_strings":["College of Electronic Engineering, Heilongjiang University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Engineering, Heilongjiang University, Harbin, China","institution_ids":["https://openalex.org/I55022517"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002128530","display_name":"Shuangcai Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I55022517","display_name":"Heilongjiang University","ror":"https://ror.org/04zyhq975","country_code":"CN","type":"education","lineage":["https://openalex.org/I55022517"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuangcai Liu","raw_affiliation_strings":["College of Electronic Engineering, Heilongjiang University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Engineering, Heilongjiang University, Harbin, China","institution_ids":["https://openalex.org/I55022517"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5110638237"],"corresponding_institution_ids":["https://openalex.org/I55022517"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":10.8032,"has_fulltext":true,"cited_by_count":136,"citation_normalized_percentile":{"value":0.98803735,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"8","issue":null,"first_page":"32826","last_page":"32839"},"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":0.9851999878883362,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7464210391044617},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7059358954429626},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6504796147346497},{"id":"https://openalex.org/keywords/retinal","display_name":"Retinal","score":0.5838870406150818},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5609376430511475},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5444804430007935},{"id":"https://openalex.org/keywords/fundus","display_name":"Fundus (uterus)","score":0.5122613310813904},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5014269351959229},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4891519844532013},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.487043172121048},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.47479313611984253},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.42020735144615173},{"id":"https://openalex.org/keywords/ophthalmology","display_name":"Ophthalmology","score":0.1768861711025238},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1330360472202301},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.061082541942596436},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.05897447466850281}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7464210391044617},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7059358954429626},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6504796147346497},{"id":"https://openalex.org/C2780827179","wikidata":"https://www.wikidata.org/wiki/Q422001","display_name":"Retinal","level":2,"score":0.5838870406150818},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5609376430511475},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5444804430007935},{"id":"https://openalex.org/C2776391266","wikidata":"https://www.wikidata.org/wiki/Q9612","display_name":"Fundus (uterus)","level":2,"score":0.5122613310813904},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5014269351959229},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4891519844532013},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.487043172121048},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.47479313611984253},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.42020735144615173},{"id":"https://openalex.org/C118487528","wikidata":"https://www.wikidata.org/wiki/Q161437","display_name":"Ophthalmology","level":1,"score":0.1768861711025238},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1330360472202301},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.061082541942596436},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.05897447466850281},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2974027","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2974027","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08999616.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:16aef13899a7458bb3a87c6b6d7fa11a","is_oa":true,"landing_page_url":"https://doaj.org/article/16aef13899a7458bb3a87c6b6d7fa11a","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 32826-32839 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2974027","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2974027","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08999616.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.7200000286102295}],"awards":[{"id":"https://openalex.org/G4399532171","display_name":null,"funder_award_id":"201806","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8031617931","display_name":null,"funder_award_id":"61573132","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3006026428.pdf","grobid_xml":"https://content.openalex.org/works/W3006026428.grobid-xml"},"referenced_works_count":58,"referenced_works":["https://openalex.org/W1660566052","https://openalex.org/W1901129140","https://openalex.org/W1901699690","https://openalex.org/W1903029394","https://openalex.org/W1912405798","https://openalex.org/W1976001975","https://openalex.org/W1984909565","https://openalex.org/W1991822469","https://openalex.org/W1993427098","https://openalex.org/W2010965043","https://openalex.org/W2016803658","https://openalex.org/W2018593404","https://openalex.org/W2019856266","https://openalex.org/W2049822456","https://openalex.org/W2089712192","https://openalex.org/W2105685332","https://openalex.org/W2106377568","https://openalex.org/W2109037308","https://openalex.org/W2118748558","https://openalex.org/W2119399382","https://openalex.org/W2125956239","https://openalex.org/W2126583464","https://openalex.org/W2132519114","https://openalex.org/W2176884330","https://openalex.org/W2206167351","https://openalex.org/W2316864010","https://openalex.org/W2395611524","https://openalex.org/W2412782625","https://openalex.org/W2433259561","https://openalex.org/W2527341761","https://openalex.org/W2587499148","https://openalex.org/W2601564443","https://openalex.org/W2749049648","https://openalex.org/W2769713325","https://openalex.org/W2789298654","https://openalex.org/W2792730533","https://openalex.org/W2800821945","https://openalex.org/W2805367842","https://openalex.org/W2809144587","https://openalex.org/W2809924268","https://openalex.org/W2893691907","https://openalex.org/W2894802018","https://openalex.org/W2898910301","https://openalex.org/W2910963184","https://openalex.org/W2913847772","https://openalex.org/W2945729873","https://openalex.org/W2951934944","https://openalex.org/W2960665958","https://openalex.org/W2963298074","https://openalex.org/W2963901018","https://openalex.org/W2979636344","https://openalex.org/W2993549925","https://openalex.org/W6637087877","https://openalex.org/W6639824700","https://openalex.org/W6640054144","https://openalex.org/W6653172889","https://openalex.org/W6678820127","https://openalex.org/W6771531534"],"related_works":["https://openalex.org/W2180954594","https://openalex.org/W2052835778","https://openalex.org/W2049003611","https://openalex.org/W2108418243","https://openalex.org/W2127804977","https://openalex.org/W164103134","https://openalex.org/W2787352659","https://openalex.org/W1970611213","https://openalex.org/W4206560911","https://openalex.org/W4372260270"],"abstract_inverted_index":{"The":[0,175],"accuracy":[1,24,161,185],"of":[2,7,13,25,28,129,150,186],"retinal":[3,38,76,187,194],"vessels":[4,29,108,188,195],"segmentation":[5,23,196],"is":[6],"great":[8],"significance":[9],"for":[10],"the":[11,22,26,34,37,56,75,92,97,101,107,122,127,137,144,148,160,184],"diagnosis":[12],"cardiovascular":[14],"diseases":[15],"such":[16],"as":[17,86],"diabetes":[18],"and":[19,61,64,125,164,171,190],"hypertension.":[20],"Especially,":[21],"end":[27],"will":[30],"be":[31],"affected":[32],"by":[33],"area":[35],"outside":[36],"in":[39,96,116,140,183],"fundus":[40],"image.":[41],"In":[42],"this":[43],"paper,":[44],"we":[45,132],"propose":[46],"an":[47,80],"attention":[48,81,105],"guided":[49],"U-Net":[50],"with":[51,159],"atrous":[52,111,138],"convolution(AA-UNet),":[53],"which":[54,83,119],"guides":[55],"model":[57,98,102,158],"to":[58,74,78,90,99,106,136,142],"separate":[59],"vessel":[60,151],"non-vessel":[62],"pixels":[63],"reuses":[65],"deep":[66],"features.":[67],"Firstly,":[68],"AA-UNet":[69],"regresses":[70],"a":[71,87],"boundary":[72],"box":[73],"region":[77],"generate":[79],"mask,":[82],"was":[84],"used":[85],"weighting":[88],"function":[89],"multiply":[91],"differential":[93],"feature":[94,117],"map":[95],"make":[100],"pay":[103],"more":[104,153],"region.":[109],"Secondly,":[110],"convolution":[112,115,139],"replaces":[113],"ordinary":[114],"layer,":[118],"can":[120],"increase":[121],"receptive":[123],"field":[124],"reduce":[126],"amount":[128],"computation.":[130],"Then,":[131],"add":[133],"two":[134],"shortcuts":[135],"order":[141],"reuse":[143],"features,":[145],"so":[146],"that":[147,178],"details":[149],"are":[152,162,166],"prominent.":[154],"We":[155],"test":[156],"our":[157,179],"0.9558/0.9640/0.9608":[163],"AUC":[165],"0.9847/0.9824/0.9865":[167],"on":[168],"DRIVE,":[169],"STARE":[170],"CHASE_DB1":[172],"datasets,":[173],"respectively.":[174],"results":[176],"show":[177],"method":[180],"has":[181],"improvement":[182],"segmentation,":[189],"exceeded":[191],"other":[192],"representative":[193],"methods.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":31},{"year":2022,"cited_by_count":35},{"year":2021,"cited_by_count":23},{"year":2020,"cited_by_count":3}],"updated_date":"2026-05-09T13:55:54.758798","created_date":"2025-10-10T00:00:00"}