{"id":"https://openalex.org/W4415708828","doi":"https://doi.org/10.1109/icme59968.2025.11209179","title":"Mutual Teaching: Semi-supervised Medical Image Classification with Cross Structural Consistency Learning","display_name":"Mutual Teaching: Semi-supervised Medical Image Classification with Cross Structural Consistency Learning","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4415708828","doi":"https://doi.org/10.1109/icme59968.2025.11209179"},"language":null,"primary_location":{"id":"doi:10.1109/icme59968.2025.11209179","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209179","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5114173805","display_name":"Chuankai Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuankai Xu","raw_affiliation_strings":["Tianjin University,College of Intelligence and Computing,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University,College of Intelligence and Computing,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101576587","display_name":"Junhao Li","orcid":"https://orcid.org/0000-0003-4752-105X"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junhao Li","raw_affiliation_strings":["Southern University of Science and Technology,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology,Shenzhen,China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065798206","display_name":"Ruxin Wang","orcid":"https://orcid.org/0000-0003-4772-3284"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruxin Wang","raw_affiliation_strings":["Chinese Academy of Sciences,Shenzhen Institutes of Advanced Technology,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Shenzhen Institutes of Advanced Technology,Shenzhen,China","institution_ids":["https://openalex.org/I4210145761"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.2071000039577484,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.2071000039577484,"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"}},{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.1370999962091446,"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":0.13449999690055847,"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/consistency","display_name":"Consistency (knowledge bases)","score":0.5716999769210815},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.555400013923645},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4198000133037567},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.3865000009536743},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36559998989105225},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3375999927520752}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6122999787330627},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5716999769210815},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.555400013923645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.546999990940094},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48570001125335693},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4198000133037567},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38909998536109924},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.3865000009536743},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36559998989105225},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3375999927520752},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.287200003862381},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.28209999203681946},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27320000529289246},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25690001249313354}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme59968.2025.11209179","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209179","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2118978333","https://openalex.org/W2133533561","https://openalex.org/W2918552801","https://openalex.org/W2955192706","https://openalex.org/W2963446712","https://openalex.org/W2990231018","https://openalex.org/W3024371423","https://openalex.org/W3164631742","https://openalex.org/W3177540946","https://openalex.org/W3211326549","https://openalex.org/W4221162144","https://openalex.org/W4295795848","https://openalex.org/W4295916111","https://openalex.org/W4306647851","https://openalex.org/W4311777178","https://openalex.org/W4312436424","https://openalex.org/W4313680901","https://openalex.org/W4323924189","https://openalex.org/W4382404966","https://openalex.org/W4386065420","https://openalex.org/W4386075941","https://openalex.org/W4389827562","https://openalex.org/W4390872874"],"related_works":[],"abstract_inverted_index":{"In":[0],"medical":[1,73,120,167],"image":[2,121,168],"analysis,":[3],"obtaining":[4],"extensive":[5,162],"well-annotated":[6],"data":[7],"is":[8,23,151],"expensive":[9],"and":[10,45,59,86,139],"laborious":[11],"in":[12,51,64,90,157],"that":[13,38,173],"it":[14],"needs":[15],"expert":[16],"knowledge":[17],"of":[18,31,72,95,128],"clinicians.":[19],"Semi-supervised":[20],"learning":[21],"(SSL)":[22],"an":[24],"effective":[25],"solution":[26],"to":[27,69,84,107,153,181],"address":[28,99],"the":[29,53,57,70,93,104,143,170,174],"scarcity":[30],"labeled":[32],"data.":[33,158],"Although":[34],"classical":[35,105],"consistency-based":[36],"methods":[37],"usually":[39],"involve":[40],"two":[41,165],"roles":[42],"(e.g.":[43],"student":[44,58],"teacher)":[46],"have":[47,160],"shown":[48],"potential":[49],"advantages":[50],"SSL,":[52],"tightly":[54],"coupled":[55],"between":[56],"teacher":[60],"models":[61],"may":[62],"result":[63],"suboptimal":[65],"performance.":[66],"Additionally,":[67],"due":[68],"complexity":[71],"images,":[74],"consistency":[75,116,149],"constraints":[76],"based":[77],"on":[78,142,164],"a":[79,108],"single":[80],"sample":[81],"are":[82],"susceptible":[83],"noise":[85],"perceived":[87],"perturbations,":[88],"which":[89,136],"turn":[91],"limit":[92],"effectiveness":[94],"semi-supervised":[96,119],"learning.":[97],"To":[98],"these":[100],"problems,":[101],"we":[102],"extend":[103],"mean-teacher":[106],"new":[109],"mutual":[110,124],"teaching":[111],"architecture":[112],"with":[113],"cross":[114],"structural":[115,147],"regularization":[117,150],"for":[118],"classification.":[122],"Through":[123],"teaching,":[125],"different":[126],"combinations":[127],"teacher-student":[129],"pairs":[130],"can":[131],"learn":[132],"from":[133],"each":[134],"other,":[135],"enhances":[137],"robustness":[138],"generalization.":[140],"Based":[141],"proposed":[144,175],"architecture,":[145],"cross-level":[146],"relation":[148],"designed":[152],"capture":[154],"higher-order":[155],"dependencies":[156],"We":[159],"conducted":[161],"experiments":[163],"public":[166],"datasets,":[169],"results":[171],"show":[172],"method":[176],"has":[177],"outstanding":[178],"performance":[179],"compared":[180],"other":[182],"state-of-the-art":[183],"approaches.":[184]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-30T00:00:00"}
