{"id":"https://openalex.org/W7125428179","doi":"https://doi.org/10.1109/tip.2026.3654402","title":"Imbalanced Multiclassification Challenges in Whole Slide Image: Cross-Patient Pseudo Bags Generation and Curriculum Contrastive Learning With Dynamic Rebalancing","display_name":"Imbalanced Multiclassification Challenges in Whole Slide Image: Cross-Patient Pseudo Bags Generation and Curriculum Contrastive Learning With Dynamic Rebalancing","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7125428179","doi":"https://doi.org/10.1109/tip.2026.3654402","pmid":"https://pubmed.ncbi.nlm.nih.gov/41564047"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2026.3654402","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3654402","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5066400057","display_name":"Yonghuang Wu","orcid":"https://orcid.org/0000-0002-5804-5573"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yonghuang Wu","raw_affiliation_strings":["School of Biomedical Engineering and Technological Innovation, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering and Technological Innovation, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xuan Xie","orcid":"https://orcid.org/0000-0002-4138-0076"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Xie","raw_affiliation_strings":["School of Biomedical Engineering and Technological Innovation, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering and Technological Innovation, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081814863","display_name":"Chengqian Zhao","orcid":"https://orcid.org/0000-0003-3860-8161"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengqian Zhao","raw_affiliation_strings":["School of Biomedical Engineering and Technological Innovation, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering and Technological Innovation, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123544615","display_name":"Pengfei Song","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengfei Song","raw_affiliation_strings":["School of Biomedical Engineering and Technological Innovation, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering and Technological Innovation, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123546639","display_name":"Feiyu Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feiyu Yin","raw_affiliation_strings":["School of Biomedical Engineering and Technological Innovation, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering and Technological Innovation, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Guoqing Wu","orcid":"https://orcid.org/0000-0002-8991-8701"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoqing Wu","raw_affiliation_strings":["School of Biomedical Engineering and Technological Innovation, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering and Technological Innovation, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123553115","display_name":"Jinhua Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhua Yu","raw_affiliation_strings":["School of Biomedical Engineering and Technological Innovation, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering and Technological Innovation, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5066400057"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16560329,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":null,"first_page":"904","last_page":"914"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9253000020980835,"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/T10862","display_name":"AI in cancer detection","score":0.9253000020980835,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.016499999910593033,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.01080000028014183,"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/sample","display_name":"Sample (material)","score":0.565500020980835},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5346999764442444},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5268999934196472},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5145000219345093},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.45969998836517334},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44350001215934753},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.43630000948905945},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.38359999656677246}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7107999920845032},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.703000009059906},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5742999911308289},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.565500020980835},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5346999764442444},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5268999934196472},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5145000219345093},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.45969998836517334},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44350001215934753},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.43630000948905945},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.38359999656677246},{"id":"https://openalex.org/C47177190","wikidata":"https://www.wikidata.org/wiki/Q207137","display_name":"Curriculum","level":2,"score":0.3456000089645386},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.34220001101493835},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3156999945640564},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.2858999967575073},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2815999984741211},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2768999934196472},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.258899986743927}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2026.3654402","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3654402","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:41564047","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41564047","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4056029687","display_name":null,"funder_award_id":"82372096","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4382424094","display_name":null,"funder_award_id":"2025YFC2423000","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2302302587","https://openalex.org/W2560886373","https://openalex.org/W2772723798","https://openalex.org/W2956228567","https://openalex.org/W2980118615","https://openalex.org/W2987301104","https://openalex.org/W3033382446","https://openalex.org/W3034534840","https://openalex.org/W3035524453","https://openalex.org/W3081006173","https://openalex.org/W3088334344","https://openalex.org/W3091730259","https://openalex.org/W3135547872","https://openalex.org/W3176719058","https://openalex.org/W3203838058","https://openalex.org/W4205991051","https://openalex.org/W4281257868","https://openalex.org/W4292325804","https://openalex.org/W4295935507","https://openalex.org/W4312468136","https://openalex.org/W4312504619","https://openalex.org/W4312765357","https://openalex.org/W4312776869","https://openalex.org/W4362658561","https://openalex.org/W4366750994","https://openalex.org/W4367295871","https://openalex.org/W4377990928","https://openalex.org/W4385064695","https://openalex.org/W4386076404","https://openalex.org/W4387225572","https://openalex.org/W4390706891","https://openalex.org/W4392947521","https://openalex.org/W4394596587","https://openalex.org/W4398201291","https://openalex.org/W4402125280"],"related_works":[],"abstract_inverted_index":{"The":[0],"multi-classification":[1],"of":[2,60,131],"histopathological":[3],"images":[4],"under":[5],"imbalanced":[6],"sample":[7,75],"conditions":[8],"remains":[9],"a":[10,26,40,95],"long-standing":[11],"unresolved":[12],"challenge":[13,59],"in":[14,39,63,135,142],"computational":[15],"pathology.":[16],"In":[17],"this":[18,33],"paper,":[19],"we":[20,66],"propose":[21,67],"for":[22],"the":[23,57,125],"first":[24],"time":[25],"cross-patient":[27,41],"pseudo-bag":[28,42,64],"generation":[29,43],"technique":[30],"to":[31,50,81,107],"address":[32,108],"challenge.":[34],"Our":[35,111],"key":[36],"innovation":[37],"lies":[38],"framework":[44,93],"that":[45],"extracts":[46],"complementary":[47],"pathological":[48],"features":[49],"construct":[51],"distributionally":[52],"consistent":[53],"pseudo-bags.":[54],"To":[55],"resolve":[56],"critical":[58],"distributional":[61],"alignment":[62],"generation,":[65],"an":[68,129],"affinity-driven":[69],"curriculum":[70],"contrastive":[71],"learning":[72],"strategy,":[73],"integrating":[74],"affinity":[76],"metrics":[77],"with":[78,120],"progressive":[79],"training":[80],"stabilize":[82],"representation":[83],"learning.":[84],"Unlike":[85],"prior":[86],"methods":[87],"focused":[88],"on":[89,117],"bag-level":[90],"embeddings,":[91],"our":[92],"pioneers":[94],"paradigm":[96],"shift":[97],"toward":[98],"multi-instance":[99],"feature":[100],"distribution":[101],"mining,":[102],"explicitly":[103],"modeling":[104],"inter-bag":[105],"heterogeneity":[106],"class":[109],"imbalance.":[110],"method":[112,127],"demonstrates":[113],"significant":[114],"performance":[115],"improvements":[116],"three":[118],"datasets":[119],"multiple":[121],"classification":[122],"difficulties,":[123],"outperforming":[124],"second-best":[126],"by":[128],"average":[130],"1.95":[132],"percentage":[133,140],"points":[134,141],"F1":[136],"score":[137],"and":[138],"2.07":[139],"ACC.":[143]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-23T00:00:00"}