{"id":"https://openalex.org/W4309675290","doi":"https://doi.org/10.1109/smc53654.2022.9945112","title":"MMF-Net: A Novel Multimodal Multiscale Fusion Network for Artery/Vein Segmentation in Retinal Fundus","display_name":"MMF-Net: A Novel Multimodal Multiscale Fusion Network for Artery/Vein Segmentation in Retinal Fundus","publication_year":2022,"publication_date":"2022-10-09","ids":{"openalex":"https://openalex.org/W4309675290","doi":"https://doi.org/10.1109/smc53654.2022.9945112"},"language":"en","primary_location":{"id":"doi:10.1109/smc53654.2022.9945112","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc53654.2022.9945112","pdf_url":null,"source":{"id":"https://openalex.org/S4363607746","display_name":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5019215450","display_name":"Junyan Yi","orcid":"https://orcid.org/0000-0002-8819-8642"},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junyan Yi","raw_affiliation_strings":["Beijing University of Civil Engineering and Architecture,Beijing,China","Beijing University of Civil Engineering and Architecture, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Civil Engineering and Architecture,Beijing,China","institution_ids":["https://openalex.org/I62853816"]},{"raw_affiliation_string":"Beijing University of Civil Engineering and Architecture, Beijing, China","institution_ids":["https://openalex.org/I62853816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009302052","display_name":"Chouyu Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chouyu Chen","raw_affiliation_strings":["Beijing University of Civil Engineering and Architecture,Beijing,China","Beijing University of Civil Engineering and Architecture, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Civil Engineering and Architecture,Beijing,China","institution_ids":["https://openalex.org/I62853816"]},{"raw_affiliation_string":"Beijing University of Civil Engineering and Architecture, Beijing, China","institution_ids":["https://openalex.org/I62853816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034103782","display_name":"Qijie Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qijie Wei","raw_affiliation_strings":["Visionary Intelligence Ltd, Vistel Inc,Beijing,China","Visionary Intelligence Ltd, Vistel Inc, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Visionary Intelligence Ltd, Vistel Inc,Beijing,China","institution_ids":["https://openalex.org/I4210100255"]},{"raw_affiliation_string":"Visionary Intelligence Ltd, Vistel Inc, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119929807","display_name":"Dayong Ding","orcid":"https://orcid.org/0009-0003-6574-2056"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dayong Ding","raw_affiliation_strings":["Visionary Intelligence Ltd, Vistel Inc,Beijing,China","Visionary Intelligence Ltd, Vistel Inc, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Visionary Intelligence Ltd, Vistel Inc,Beijing,China","institution_ids":["https://openalex.org/I4210100255"]},{"raw_affiliation_string":"Visionary Intelligence Ltd, Vistel Inc, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002627939","display_name":"Gang Yang","orcid":"https://orcid.org/0000-0003-0765-6769"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Yang","raw_affiliation_strings":["Renmin University of China,Information School,Beijing,China","Information School, Renmin University of China, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Renmin University of China,Information School,Beijing,China","institution_ids":["https://openalex.org/I78988378"]},{"raw_affiliation_string":"Information School, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5019215450"],"corresponding_institution_ids":["https://openalex.org/I62853816"],"apc_list":null,"apc_paid":null,"fwci":0.2214,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.46150403,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1192","last_page":"1197"},"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":0.9879000186920166,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9807000160217285,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.79710853099823},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.732812225818634},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7090080976486206},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6967602968215942},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5775241851806641},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.525887668132782},{"id":"https://openalex.org/keywords/fundus","display_name":"Fundus (uterus)","score":0.5252644419670105},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.496296226978302},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.47132638096809387},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.44149500131607056},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4069386124610901},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.05820539593696594}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.79710853099823},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.732812225818634},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7090080976486206},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6967602968215942},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5775241851806641},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.525887668132782},{"id":"https://openalex.org/C2776391266","wikidata":"https://www.wikidata.org/wiki/Q9612","display_name":"Fundus (uterus)","level":2,"score":0.5252644419670105},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.496296226978302},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.47132638096809387},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.44149500131607056},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4069386124610901},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.05820539593696594},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc53654.2022.9945112","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc53654.2022.9945112","pdf_url":null,"source":{"id":"https://openalex.org/S4363607746","display_name":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321572","display_name":"Beijing Municipal Commission of Education","ror":"https://ror.org/04bpn6s66"},{"id":"https://openalex.org/F4320325174","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1968535857","https://openalex.org/W2001885074","https://openalex.org/W2093545979","https://openalex.org/W2117935664","https://openalex.org/W2163344010","https://openalex.org/W2174711832","https://openalex.org/W2194775991","https://openalex.org/W2205926907","https://openalex.org/W2270168057","https://openalex.org/W2763797438","https://openalex.org/W2800539275","https://openalex.org/W2915212708","https://openalex.org/W2923997689","https://openalex.org/W2928165649","https://openalex.org/W2962189327","https://openalex.org/W2963420686","https://openalex.org/W2979430722","https://openalex.org/W3001319304","https://openalex.org/W3037875018","https://openalex.org/W3172603679","https://openalex.org/W4385245566","https://openalex.org/W6639824700","https://openalex.org/W6739901393","https://openalex.org/W6743731764","https://openalex.org/W6761176859"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W4230315250","https://openalex.org/W2086519370","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Automatic":[0],"artery/vein":[1],"(Arkers":[2],"for":[3],"the":[4,21,27,43,48,57,61,71,75,81,87,94,104,109,127,135,161],"early":[5],"diagnosis":[6],"of":[7,23,52,89,137,163],"many":[8],"systemic":[9],"diseases.":[10],"Unfortunately,":[11],"current":[12],"methods":[13,159],"have":[14],"some":[15],"limitations":[16],"in":[17,121,160],"AN":[18,58,82,138,164],"segmentation,":[19],"especially":[20],"lack":[22],"annotated":[24],"data":[25,29],"and":[26,125,154],"serious":[28],"imbalance.":[30],"Thus,":[31],"A":[32,114],"novel":[33],"multimodal":[34,65,110],"multiscale":[35,98],"fusion":[36,116],"network":[37],"(MMF-Net)":[38],"is":[39,119],"proposed":[40],"to":[41,55,79,102,123,133],"alleviate":[42],"above":[44],"problems,":[45],"which":[46,85],"utilizes":[47],"internal":[49],"semantic":[50],"information":[51,106],"vessels":[53],"adequately":[54],"enhance":[56],"segmentation.":[59,139,165],"Particularly,":[60],"MMF-Net":[62,95,122],"introduces":[63],"a":[64,97],"(MM)":[66],"module":[67,101,118],"that":[68,147],"could":[69],"highlight":[70],"vessel":[72,105],"structure":[73],"from":[74,108,130],"original":[76],"fundus":[77],"image":[78,83],"constrain":[80],"features,":[84],"reduces":[86],"influence":[88],"background":[90],"noise.":[91],"In":[92],"addition,":[93],"exploits":[96],"transformation":[99],"(MT)":[100],"extract":[103],"efficiently":[107],"feature":[111,129],"representations.":[112],"Finally,":[113],"multi-feature":[115],"(MF)":[117],"applied":[120],"split":[124],"reorganize":[126],"pixel":[128],"different":[131],"scales":[132],"improve":[134],"robustness":[136],"Experiments":[140],"on":[141],"two":[142],"public":[143],"benchmark":[144],"datasets":[145],"show":[146],"our":[148],"method":[149],"has":[150],"achieved":[151],"superior":[152],"performance":[153],"surpassed":[155],"other":[156],"existing":[157],"state-of-the-art":[158],"accuracy":[162]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-16T08:24:45.110214","created_date":"2025-10-10T00:00:00"}