{"id":"https://openalex.org/W4225709022","doi":"https://doi.org/10.1109/bibm52615.2021.9669490","title":"PAENet: A Progressive Attention-Enhanced Network for 3D to 2D Retinal Vessel Segmentation","display_name":"PAENet: A Progressive Attention-Enhanced Network for 3D to 2D Retinal Vessel Segmentation","publication_year":2021,"publication_date":"2021-12-09","ids":{"openalex":"https://openalex.org/W4225709022","doi":"https://doi.org/10.1109/bibm52615.2021.9669490"},"language":"en","primary_location":{"id":"doi:10.1109/bibm52615.2021.9669490","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm52615.2021.9669490","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/A5035339014","display_name":"Zhuojie Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhuojie Wu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100371696","display_name":"Zijian Wang","orcid":"https://orcid.org/0000-0001-5777-9594"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zijian Wang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049289977","display_name":"Wenxuan Zou","orcid":"https://orcid.org/0000-0002-6945-3513"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxuan Zou","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089736686","display_name":"Fan Ji","orcid":"https://orcid.org/0009-0007-3068-4158"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Ji","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101802746","display_name":"Hao Dang","orcid":"https://orcid.org/0000-0001-5861-6535"},"institutions":[{"id":"https://openalex.org/I4210155511","display_name":"First Affiliated Hospital of Henan University","ror":"https://ror.org/0536rsk67","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210155511"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Dang","raw_affiliation_strings":["Henan University of Chinese Medicine, Henan, China"],"affiliations":[{"raw_affiliation_string":"Henan University of Chinese Medicine, Henan, China","institution_ids":["https://openalex.org/I4210155511"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040993283","display_name":"Wanting Zhou","orcid":"https://orcid.org/0000-0003-0867-4117"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanting Zhou","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084960489","display_name":"Muyi Sun","orcid":"https://orcid.org/0000-0001-9506-7643"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Muyi Sun","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5035339014"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":2.7303,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.91320755,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1579","last_page":"1584"},"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/T10170","display_name":"Retinal Diseases and Treatments","score":0.9937999844551086,"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/T10250","display_name":"Glaucoma and retinal disorders","score":0.993399977684021,"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/computer-science","display_name":"Computer science","score":0.7496482133865356},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7118328809738159},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.704332709312439},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6939218044281006},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.606957197189331},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5474725961685181},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.47501763701438904},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4585319757461548},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.43796342611312866},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.413917601108551},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10561588406562805}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7496482133865356},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7118328809738159},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.704332709312439},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6939218044281006},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.606957197189331},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5474725961685181},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47501763701438904},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4585319757461548},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.43796342611312866},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.413917601108551},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10561588406562805},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm52615.2021.9669490","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm52615.2021.9669490","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1199446928","https://openalex.org/W1992868980","https://openalex.org/W2010965043","https://openalex.org/W2087681061","https://openalex.org/W2100756624","https://openalex.org/W2150769593","https://openalex.org/W2163344010","https://openalex.org/W2527341761","https://openalex.org/W2556022279","https://openalex.org/W2561516185","https://openalex.org/W2801013643","https://openalex.org/W2884585870","https://openalex.org/W2955058313","https://openalex.org/W2963091558","https://openalex.org/W2963420686","https://openalex.org/W3023476182","https://openalex.org/W3089571734","https://openalex.org/W3113013200","https://openalex.org/W3119205652","https://openalex.org/W3159991667","https://openalex.org/W3161081823","https://openalex.org/W3165739880","https://openalex.org/W3181955139","https://openalex.org/W6653172889","https://openalex.org/W6743731764","https://openalex.org/W6753412334","https://openalex.org/W6787510147","https://openalex.org/W6798274885"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W147410782","https://openalex.org/W3022252430","https://openalex.org/W3103989898","https://openalex.org/W4287804464","https://openalex.org/W803346624","https://openalex.org/W3021077427"],"abstract_inverted_index":{"3D":[0,37,174],"to":[1,65,160,172,188],"2D":[2,178],"retinal":[3,18],"vessel":[4,19],"segmentation":[5,20,49,86,158],"is":[6,21,42],"a":[7,43,56,96,104,122,167],"challenging":[8],"problem":[9],"in":[10,193],"Optical":[11],"Coherence":[12],"Tomography":[13],"Angiography":[14],"(OCTA)":[15],"images.":[16],"Accurate":[17],"important":[22],"for":[23,46,127],"the":[24,36,71,78,84,89,115,137,140,156,177,183,190,204],"diagnosis":[25],"and":[26,83,102,120,195],"prevention":[27],"of":[28,35,39,74,118,124,151],"ophthalmic":[29],"diseases.":[30],"However,":[31],"making":[32],"full":[33],"use":[34,150],"data":[38],"OCTA":[40],"volumes":[41,119],"vital":[44],"factor":[45],"obtaining":[47],"satisfactory":[48],"results.":[50],"In":[51,88,135,155],"this":[52],"paper,":[53],"we":[54,94,165,181],"propose":[55,103,166],"Progressive":[57],"Attention-Enhanced":[58],"Network":[59],"(PAENet)":[60],"based":[61],"on":[62,203],"attention":[63],"mechanisms":[64],"extract":[66],"rich":[67],"feature":[68,80,91,128,133,153],"representation.":[69],"Specifically,":[70],"framework":[72],"consists":[73],"two":[75],"main":[76],"parts,":[77],"three-dimensional":[79,90],"learning":[81,92],"path":[82],"two-dimensional":[85,157],"path.":[87,179],"path,":[93,159],"design":[95],"novel":[97],"Adaptive":[98],"Pooling":[99],"Module":[100,108,170],"(APM)":[101],"new":[105],"Quadruple":[106],"Attention":[107],"(QAM).":[109],"The":[110],"APM":[111],"captures":[112],"dependencies":[113],"along":[114],"projection":[116],"direction":[117],"learns":[121],"series":[123],"pooling":[125],"coefficients":[126],"fusion,":[129],"which":[130,147],"efficiently":[131],"reduces":[132],"dimension.":[134],"addition,":[136],"QAM":[138],"reweights":[139],"features":[141],"by":[142],"capturing":[143],"four-group":[144],"cross-dimension":[145],"dependencies,":[146],"makes":[148],"maximum":[149],"4D":[152],"tensors.":[154],"acquire":[161],"more":[162],"detailed":[163],"information,":[164],"Feature":[168],"Fusion":[169],"(FFM)":[171],"inject":[173],"information":[175],"into":[176],"Meanwhile,":[180],"adopt":[182],"Polarized":[184],"Self-Attention":[185],"(PSA)":[186],"block":[187],"model":[189],"semantic":[191],"interdependencies":[192],"spatial":[194],"channel":[196],"dimensions":[197],"respectively.":[198],"Experimentally,":[199],"our":[200,209],"extensive":[201],"experiments":[202],"OCTA-500":[205],"dataset":[206],"show":[207],"that":[208],"proposed":[210],"algorithm":[211],"achieves":[212],"state-of-the-art":[213],"performance":[214],"compared":[215],"with":[216],"previous":[217],"methods.":[218]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
