{"id":"https://openalex.org/W4392903785","doi":"https://doi.org/10.1109/icassp48485.2024.10447013","title":"Contrmix: Progressive Mixed Contrastive Learning for Semi-Supervised Medical Image Segmentation","display_name":"Contrmix: Progressive Mixed Contrastive Learning for Semi-Supervised Medical Image Segmentation","publication_year":2024,"publication_date":"2024-03-18","ids":{"openalex":"https://openalex.org/W4392903785","doi":"https://doi.org/10.1109/icassp48485.2024.10447013"},"language":"en","primary_location":{"id":"doi:10.1109/icassp48485.2024.10447013","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10447013","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 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/A5015106862","display_name":"Meisheng Zhang","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":"Meisheng Zhang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China","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"]},{"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/A5102845757","display_name":"Chenye Wang","orcid":"https://orcid.org/0000-0002-2412-0870"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenye Wang","raw_affiliation_strings":["Beijing Normal University,Beijing,China","Beijing Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Normal University,Beijing,China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"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/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxuan Zou","raw_affiliation_strings":["Beihang University,Beijing,China","Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University,Beijing,China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026841385","display_name":"Xingqun Qi","orcid":"https://orcid.org/0000-0002-9772-5707"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xingqun Qi","raw_affiliation_strings":["The Hong Kong University of Science and Technology,Hong Kong,China","The Hong Kong University of Science and Technology, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology,Hong Kong,China","institution_ids":["https://openalex.org/I200769079"]},{"raw_affiliation_string":"The Hong Kong University of Science and Technology, Hong Kong, China","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084960489","display_name":"Muyi Sun","orcid":"https://orcid.org/0000-0001-9506-7643"},"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"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","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":["Beijing University of Posts and Telecommunications,Beijing,China","Institute of Automation, Chinese Academy of Sciences, Beijing, China","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"]},{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]},{"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/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","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"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5015106862"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":1.1758,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.77120767,"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":"2260","last_page":"2264"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9947999715805054,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9947999715805054,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9873999953269958,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.7582203149795532},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7068489193916321},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6719872951507568},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6134174466133118},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5145475268363953},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46942952275276184},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45714452862739563},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3499656617641449},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3135525584220886}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7582203149795532},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7068489193916321},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6719872951507568},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6134174466133118},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5145475268363953},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46942952275276184},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45714452862739563},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3499656617641449},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3135525584220886}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp48485.2024.10447013","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10447013","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-138260","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-138260","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2082826544","display_name":null,"funder_award_id":"Postdoctoral","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G305947982","display_name":null,"funder_award_id":"62376037","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3085993365","display_name":null,"funder_award_id":"(Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4020255992","display_name":null,"funder_award_id":"Project","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5249178904","display_name":null,"funder_award_id":"Grant No. 6","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7836423780","display_name":null,"funder_award_id":"Liaoning","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8955622099","display_name":null,"funder_award_id":"62006227","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"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2804047627","https://openalex.org/W2953070460","https://openalex.org/W2962914239","https://openalex.org/W2979907638","https://openalex.org/W2992308087","https://openalex.org/W3031923721","https://openalex.org/W3044738063","https://openalex.org/W3083779147","https://openalex.org/W3093394156","https://openalex.org/W3096851030","https://openalex.org/W3097499499","https://openalex.org/W3194662286","https://openalex.org/W3203046931","https://openalex.org/W3203488660","https://openalex.org/W4214961286","https://openalex.org/W4225895868","https://openalex.org/W4287322212","https://openalex.org/W4307823382","https://openalex.org/W4381714564","https://openalex.org/W4386075748","https://openalex.org/W4402716435","https://openalex.org/W6733814495","https://openalex.org/W6853848324","https://openalex.org/W6859323018"],"related_works":["https://openalex.org/W1603736412","https://openalex.org/W2375480909","https://openalex.org/W4304185162","https://openalex.org/W2353314428","https://openalex.org/W4379231730","https://openalex.org/W2061685118","https://openalex.org/W3006282800","https://openalex.org/W2462100143","https://openalex.org/W2012019886","https://openalex.org/W1770503332"],"abstract_inverted_index":{"While":[0],"medical":[1,34,97],"image":[2],"segmentation":[3,80],"has":[4],"achieved":[5],"impressive":[6],"progress,":[7],"it":[8],"usually":[9],"being":[10],"constrained":[11],"by":[12],"labor-intensive":[13],"and":[14,27,55,81,116,133,150,153],"costly":[15],"pixel-wise":[16],"annotations.":[17],"The":[18],"existing":[19],"semi-supervised":[20,159],"learning":[21],"methods":[22],"ignore":[23],"the":[24,38,75,78,88,95,109,113,117,122,135,147],"inherent":[25],"imbalance":[26],"high":[28,139],"similarity":[29,140],"of":[30,94,138],"different":[31,131],"categories":[32],"in":[33],"images.":[35],"To":[36],"address":[37],"above":[39],"issues,":[40],"we":[41],"present":[42],"a":[43,52,56,63,68,102],"Progressive":[44],"Mixed":[45],"Contrastive":[46,58,104],"Learning":[47,59,105],"(ContrMix)":[48],"framework,":[49],"which":[50,120],"contains":[51],"Cycle-mix":[53],"module":[54,106],"mix-based":[57,103],"module.":[60],"In":[61],"Cycle-mix,":[62],"progressive":[64],"mixing":[65,84],"strategy":[66],"with":[67],"cycle":[69],"loss":[70],"is":[71],"designed":[72],"to":[73,90,124],"enforce":[74],"consistency":[76],"between":[77,112],"mixed":[79,114],"corresponding":[82],"generated":[83],"samples,":[85],"effectively":[86],"enhancing":[87],"ability":[89],"learn":[91,125],"geometric":[92],"features":[93],"imbalanced":[96],"data.":[98],"We":[99,142],"also":[100],"introduce":[101],"that":[107],"learns":[108],"inter-instance":[110],"similarities":[111],"patches":[115],"original":[118],"ones,":[119],"encourages":[121],"model":[123],"background-invariant":[126],"representations":[127],"from":[128],"samples":[129],"under":[130],"distortions":[132],"improves":[134],"semantic":[136],"discrimination":[137],"categories.":[141],"conduct":[143],"extensive":[144],"experiments":[145],"on":[146],"ACDC":[148],"dataset":[149,152],"LA":[151],"our":[154],"method":[155],"outperforms":[156],"other":[157],"state-of-the-art":[158],"approaches.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2025-10-10T00:00:00"}