{"id":"https://openalex.org/W4372349701","doi":"https://doi.org/10.1109/icassp49357.2023.10095868","title":"DB-UNet: MLP Based Dual Branch UNet for Accurate Vessel Segmentation in OCTA Images","display_name":"DB-UNet: MLP Based Dual Branch UNet for Accurate Vessel Segmentation in OCTA Images","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372349701","doi":"https://doi.org/10.1109/icassp49357.2023.10095868"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10095868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10095868","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5014633229","display_name":"Chengliang Wang","orcid":"https://orcid.org/0000-0003-0877-1064"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chengliang Wang","raw_affiliation_strings":["Chongqing University,School of Computer Science,Chongqing,China","School of Computer Science, Chongqing University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University,School of Computer Science,Chongqing,China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"School of Computer Science, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025642467","display_name":"Haojian Ning","orcid":null},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haojian Ning","raw_affiliation_strings":["Chongqing University,School of Computer Science,Chongqing,China","School of Computer Science, Chongqing University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University,School of Computer Science,Chongqing,China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"School of Computer Science, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084200523","display_name":"Xinrun Chen","orcid":"https://orcid.org/0000-0001-8982-9330"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinrun Chen","raw_affiliation_strings":["Chongqing University,School of Computer Science,Chongqing,China","School of Computer Science, Chongqing University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University,School of Computer Science,Chongqing,China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"School of Computer Science, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100680484","display_name":"Shiying Li","orcid":"https://orcid.org/0000-0001-9783-9520"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiying Li","raw_affiliation_strings":["Eye Institute of Xiamen University,Xiamen,China","Eye Institute of Xiamen University, Xiamen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Eye Institute of Xiamen University,Xiamen,China","institution_ids":["https://openalex.org/I191208505"]},{"raw_affiliation_string":"Eye Institute of Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5014633229"],"corresponding_institution_ids":["https://openalex.org/I158842170"],"apc_list":null,"apc_paid":null,"fwci":2.063,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.86822958,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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/T11569","display_name":"Optical Coherence Tomography Applications","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10250","display_name":"Glaucoma and retinal disorders","score":0.9933000206947327,"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/segmentation","display_name":"Segmentation","score":0.8029027581214905},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7299933433532715},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.71938556432724},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5214330554008484},{"id":"https://openalex.org/keywords/optical-coherence-tomography","display_name":"Optical coherence tomography","score":0.5060543417930603},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4910109341144562},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.47873732447624207},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44255462288856506},{"id":"https://openalex.org/keywords/retina","display_name":"Retina","score":0.4292908310890198},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.07336336374282837}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8029027581214905},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7299933433532715},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.71938556432724},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5214330554008484},{"id":"https://openalex.org/C2778818243","wikidata":"https://www.wikidata.org/wiki/Q899552","display_name":"Optical coherence tomography","level":2,"score":0.5060543417930603},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4910109341144562},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.47873732447624207},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44255462288856506},{"id":"https://openalex.org/C2777093970","wikidata":"https://www.wikidata.org/wiki/Q169342","display_name":"Retina","level":2,"score":0.4292908310890198},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.07336336374282837},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10095868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10095868","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2061273505","https://openalex.org/W2129074598","https://openalex.org/W2194775991","https://openalex.org/W2602551394","https://openalex.org/W2741520251","https://openalex.org/W2774320778","https://openalex.org/W2804416181","https://openalex.org/W2905416757","https://openalex.org/W2949846184","https://openalex.org/W3111741353","https://openalex.org/W3113013200","https://openalex.org/W3157506437","https://openalex.org/W3184094570","https://openalex.org/W3186979696","https://openalex.org/W3199556854","https://openalex.org/W4226334005","https://openalex.org/W4284976083","https://openalex.org/W4294226146","https://openalex.org/W4295934721","https://openalex.org/W4312609195","https://openalex.org/W6639824700","https://openalex.org/W6729983426","https://openalex.org/W6748775820","https://openalex.org/W6787510147","https://openalex.org/W6795140394","https://openalex.org/W6798983732","https://openalex.org/W6799423381","https://openalex.org/W6802713316"],"related_works":["https://openalex.org/W2362796209","https://openalex.org/W2348498086","https://openalex.org/W3093461874","https://openalex.org/W2027168247","https://openalex.org/W1000914229","https://openalex.org/W2038488634","https://openalex.org/W3021342607","https://openalex.org/W2488331324","https://openalex.org/W2323668004","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Optical":[0],"coherence":[1],"tomography":[2],"angiography":[3],"(OCTA)":[4],"is":[5,100],"a":[6,69,76,87,114],"new":[7],"non-invasive":[8],"imaging":[9],"technology":[10],"that":[11,135],"has":[12,75,139],"been":[13],"widely":[14],"used":[15],"in":[16,24],"clinical":[17],"practice.":[18],"Automatic":[19],"segmentation":[20,49,132,141],"of":[21,32,43,56,97,105,124],"retina":[22,44],"vessels":[23],"OCTA":[25,130],"images":[26],"helps":[27],"to":[28,37,79,90,119],"improve":[29,121],"the":[30,38,98,103,106,122,136],"efficiency":[31],"disease":[33],"diagnosis.":[34],"However,":[35],"due":[36],"slender":[39],"and":[40,54,86,112],"tiny":[41],"structure":[42],"vessels,":[45],"classical":[46],"deep":[47],"learning":[48],"methods,":[50],"such":[51,83],"as":[52,84],"UNet":[53,72,88],"some":[55],"its":[57],"variants,":[58],"cannot":[59],"handle":[60],"it":[61],"very":[62],"accurately.":[63],"In":[64],"this":[65],"work,":[66],"we":[67],"propose":[68],"dual":[70],"branch":[71,78,89],"(DB-UNet),":[73],"which":[74],"pure-convolutional":[77],"extract":[80,91],"detailed":[81],"features":[82],"microvessels,":[85],"high-level":[92],"features.":[93],"The":[94],"final":[95],"output":[96],"network":[99],"synthesized":[101],"from":[102],"outputs":[104],"two":[107,129],"branches.":[108],"We":[109],"also":[110],"design":[111],"apply":[113],"multilayer":[115],"perceptron":[116],"(MLP)":[117],"block":[118],"further":[120],"performance":[123,142],"our":[125],"model.":[126],"Experiments":[127],"on":[128],"vessel":[131],"datasets":[133],"show":[134],"proposed":[137],"method":[138],"better":[140],"than":[143],"existing":[144],"methods.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4}],"updated_date":"2026-05-01T08:36:08.643496","created_date":"2025-10-10T00:00:00"}