{"id":"https://openalex.org/W4401751253","doi":"https://doi.org/10.1109/isbi56570.2024.10635111","title":"Source-Free Semi-Supervised Domain Adaptation for Tuberculosis Recognition","display_name":"Source-Free Semi-Supervised Domain Adaptation for Tuberculosis Recognition","publication_year":2024,"publication_date":"2024-05-27","ids":{"openalex":"https://openalex.org/W4401751253","doi":"https://doi.org/10.1109/isbi56570.2024.10635111"},"language":"en","primary_location":{"id":"doi:10.1109/isbi56570.2024.10635111","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/isbi56570.2024.10635111","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Biomedical Imaging (ISBI)","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/A5100676363","display_name":"Jie Ma","orcid":"https://orcid.org/0000-0002-7570-9554"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Ma","raw_affiliation_strings":["Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050549724","display_name":"Zhijun Xu","orcid":"https://orcid.org/0000-0001-6515-2724"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijun Xu","raw_affiliation_strings":["Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107459755","display_name":"Xinyu Xiong","orcid":"https://orcid.org/0009-0004-7674-6594"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Xiong","raw_affiliation_strings":["Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029969170","display_name":"Mayidili Nijiati","orcid":"https://orcid.org/0000-0002-1346-6921"},"institutions":[{"id":"https://openalex.org/I4210162809","display_name":"Kashi University","ror":"https://ror.org/055a4rj94","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162809"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"MaYiDiLi NiJiaTi","raw_affiliation_strings":["The First People&#x2019;s Hospital of Kashi (Kashgar),Department of Radiology,Prefecture,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The First People&#x2019;s Hospital of Kashi (Kashgar),Department of Radiology,Prefecture,China","institution_ids":["https://openalex.org/I4210162809"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101973679","display_name":"Dongyu Zhang","orcid":"https://orcid.org/0000-0002-7683-5560"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongyu Zhang","raw_affiliation_strings":["Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065304272","display_name":"Weijun Sun","orcid":"https://orcid.org/0000-0002-2342-4434"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weijun Sun","raw_affiliation_strings":["Guangdong University of Technology,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045500611","display_name":"Feng Gao","orcid":"https://orcid.org/0000-0002-0500-5527"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210093460","display_name":"Sixth Affiliated Hospital of Sun Yat-sen University","ror":"https://ror.org/005pe1772","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210093460"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Gao","raw_affiliation_strings":["Sun Yat-sen University,The Sixth Affiliated Hospital,Department of General Surgery (Department of Colorectal Surgery),Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,The Sixth Affiliated Hospital,Department of General Surgery (Department of Colorectal Surgery),Guangzhou,China","institution_ids":["https://openalex.org/I4210093460","https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101691639","display_name":"Guanbin Li","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanbin Li","raw_affiliation_strings":["Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7317,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.72829986,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"34","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9988999962806702,"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":0.9988999962806702,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9610000252723694,"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/domain-adaptation","display_name":"Domain adaptation","score":0.7534044981002808},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7204639315605164},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5950992107391357},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5278035402297974},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4685222804546356},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33551180362701416},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07607784867286682},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07283943891525269}],"concepts":[{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.7534044981002808},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7204639315605164},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5950992107391357},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5278035402297974},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4685222804546356},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33551180362701416},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07607784867286682},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07283943891525269},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi56570.2024.10635111","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/isbi56570.2024.10635111","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321160","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1836465849","https://openalex.org/W1904878066","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2962858109","https://openalex.org/W2986381065","https://openalex.org/W3034922525","https://openalex.org/W3106895564","https://openalex.org/W3178144784","https://openalex.org/W4226239659","https://openalex.org/W4283810430","https://openalex.org/W4295795837","https://openalex.org/W4296196007","https://openalex.org/W4386362790","https://openalex.org/W4389664825","https://openalex.org/W4390874136","https://openalex.org/W4392910013","https://openalex.org/W6687400500","https://openalex.org/W6695676441","https://openalex.org/W6797896318","https://openalex.org/W6802028791"],"related_works":["https://openalex.org/W4394775207","https://openalex.org/W4389474468","https://openalex.org/W2033914206","https://openalex.org/W2042327336","https://openalex.org/W4300172004","https://openalex.org/W4321649381","https://openalex.org/W2997645659","https://openalex.org/W3180787869","https://openalex.org/W3203792196","https://openalex.org/W2955455867"],"abstract_inverted_index":{"Tuberculosis":[0],"(TB)":[1],"as":[2,131],"one":[3],"of":[4,15,74,102,145],"the":[5,72,95,119,143],"major":[6],"threats":[7],"to":[8,13,47,67],"human":[9],"health":[10],"worldwide,":[11],"leads":[12,46],"millions":[14],"deaths":[16],"every":[17],"year.":[18],"Despite":[19],"numerous":[20],"recent":[21],"research":[22],"efforts":[23],"towards":[24],"computer-aided":[25],"TB":[26,92],"diagnosis,":[27],"these":[28,79],"methods":[29],"often":[30],"suffer":[31],"from":[32],"data":[33,61,68],"bias,":[34],"or":[35],"domain":[36,75],"shift,":[37],"across":[38],"different":[39],"imaging":[40],"devices":[41],"and":[42,60,70,109],"hospitals.":[43],"This":[44],"limitation":[45],"poor":[48],"performance":[49],"in":[50,81],"real-world":[51],"scenarios,":[52],"especially":[53],"for":[54,91],"multi-domain":[55],"data.":[56],"Moreover,":[57],"patient":[58],"privacy":[59],"security":[62],"concerns":[63],"pose":[64],"significant":[65],"barriers":[66],"accessibility":[69],"exacerbate":[71],"difficulty":[73],"adaptation.":[76],"To":[77],"mitigate":[78],"problems,":[80],"this":[82],"paper,":[83],"we":[84],"propose":[85],"a":[86,103,110,132],"Bilateral-Branch":[87],"Consistency":[88],"Network":[89],"(BBCN)":[90],"recognition":[93],"under":[94],"Source-Free":[96],"Semi-Supervised":[97],"setting.":[98],"The":[99],"BBCN":[100],"consists":[101],"Source":[104],"Model":[105,112],"Adaptation":[106],"branch":[107,115],"(SMA)":[108],"Target":[111],"Learning":[113],"(TML)":[114],"that":[116],"effectively":[117],"enhances":[118],"cross-domain":[120,133],"feature":[121],"representation":[122],"ability.":[123],"A":[124],"consistent":[125],"regularizer":[126],"is":[127],"further":[128],"proposed":[129],"acting":[130],"regularization":[134],"interaction":[135],"machine":[136],"between":[137],"two":[138],"branches.":[139],"Experimental":[140],"results":[141],"demonstrate":[142],"effectiveness":[144],"our":[146],"method.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
