{"id":"https://openalex.org/W4416582610","doi":"https://doi.org/10.1109/tetci.2025.3631709","title":"Cross-Domain Self-Supervised Learning for Histopathological Images With Multi-Granularity Constraints","display_name":"Cross-Domain Self-Supervised Learning for Histopathological Images With Multi-Granularity Constraints","publication_year":2025,"publication_date":"2025-11-24","ids":{"openalex":"https://openalex.org/W4416582610","doi":"https://doi.org/10.1109/tetci.2025.3631709"},"language":"en","primary_location":{"id":"doi:10.1109/tetci.2025.3631709","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2025.3631709","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"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 Emerging Topics in Computational Intelligence","raw_type":"journal-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/A5070240687","display_name":"Yating Huang","orcid":"https://orcid.org/0000-0003-2024-3491"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yating Huang","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, The University of Manchester, Oxford Road, Manchester, U.K"],"raw_orcid":"https://orcid.org/0000-0003-2024-3491","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The University of Manchester, Oxford Road, Manchester, U.K","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086598677","display_name":"Dougal Ferguson","orcid":"https://orcid.org/0000-0002-4766-5339"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Dougal Ferguson","raw_affiliation_strings":["Department of Chemical Engineering, The University of Manchester, Oxford Road, Manchester, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering, The University of Manchester, Oxford Road, Manchester, U.K","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005044154","display_name":"Ashwin Sachdeva","orcid":"https://orcid.org/0000-0002-7359-7114"},"institutions":[{"id":"https://openalex.org/I4210133995","display_name":"The Christie NHS Foundation Trust","ror":"https://ror.org/03v9efr22","country_code":"GB","type":"funder","lineage":["https://openalex.org/I4210133995"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ashwin Sachdeva","raw_affiliation_strings":["Department of Surgery, The Christie NHS Foundation Trust & Division of Cancer Sciences, The University of Manchester, Oxford Road, Manchester, U.K"],"raw_orcid":"https://orcid.org/0000-0002-7359-7114","affiliations":[{"raw_affiliation_string":"Department of Surgery, The Christie NHS Foundation Trust & Division of Cancer Sciences, The University of Manchester, Oxford Road, Manchester, U.K","institution_ids":["https://openalex.org/I4210133995"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021098743","display_name":"Peter Gardner","orcid":"https://orcid.org/0000-0003-4034-3764"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Peter Gardner","raw_affiliation_strings":["Department of Chemical Engineering, The University of Manchester, Oxford Road, Manchester, U.K"],"raw_orcid":"https://orcid.org/0000-0003-4034-3764","affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering, The University of Manchester, Oxford Road, Manchester, U.K","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055149475","display_name":"Hujun Yin","orcid":"https://orcid.org/0000-0002-9198-5401"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hujun Yin","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, The University of Manchester, Oxford Road, Manchester, U.K"],"raw_orcid":"https://orcid.org/0000-0002-9198-5401","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The University of Manchester, Oxford Road, Manchester, U.K","institution_ids":["https://openalex.org/I28407311"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18619819,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":"2","first_page":"1352","last_page":"1364"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.8799999952316284,"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":0.8799999952316284,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.04390000179409981,"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":0.0071000000461936,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.722100019454956},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5651000142097473},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5494999885559082},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5335000157356262},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5101000070571899},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5080000162124634},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4375},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4214000105857849}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7832000255584717},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.722100019454956},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6851999759674072},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5651000142097473},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5494999885559082},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5335000157356262},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5131999850273132},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5101000070571899},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5080000162124634},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4375},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4214000105857849},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.4068000018596649},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.4068000018596649},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.38580000400543213},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.37290000915527344},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3294000029563904},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.319599986076355},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.3050000071525574},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.303600013256073},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.28700000047683716},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.26499998569488525}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tetci.2025.3631709","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2025.3631709","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"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 Emerging Topics in Computational Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:publications/caff8d5c-0f6a-4b13-8a9a-c7cd0857934c","is_oa":false,"landing_page_url":"https://research.manchester.ac.uk/en/publications/caff8d5c-0f6a-4b13-8a9a-c7cd0857934c","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Huang, Y, Ferguson, D, Sachdeva, A, Gardner, P & Yin, H 2025, 'Cross-Domain Self-Supervised Learning for Histopathological Images with Multi-Granularity Constraints', IEEE Transactions on Emerging Topics in Computational Intelligence.","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0,130],"pathological":[1],"image":[2],"analysis,":[3],"the":[4,10,22,32,54,152,166,183,187],"scarcity":[5],"of":[6,12,15,24,34,41,56,155,182,196],"labeled":[7],"data":[8,95],"and":[9,69,110,123,163,216],"difficulty":[11],"producing":[13],"scores":[14],"annotated":[16,220],"images":[17,157],"to":[18,46,81,91,121,150,164],"high-level":[19],"details":[20],"hinder":[21],"development":[23],"large,":[25],"high-quality":[26],"datasets,":[27],"which":[28],"in":[29,63,94,126,158,193,213],"turn":[30],"affects":[31],"advancement":[33],"deep":[35],"learning-based":[36],"diagnostic":[37],"tools.":[38],"The":[39,180,206],"lack":[40],"annotations":[42],"can":[43,105],"be":[44],"addressed":[45],"some":[47],"extent":[48],"by":[49],"self-supervised":[50,66,138],"learning":[51,67,72,139],"methods,":[52],"leveraging":[53],"production":[55],"general":[57,70],"representations":[58],"from":[59,75,84],"unlabeled":[60],"data.":[61],"However,":[62],"such":[64],"deployment,":[65],"methods":[68,117,189],"machine":[71],"models":[73],"suffer":[74],"significant":[76],"performance":[77],"degradation":[78],"when":[79],"transferring":[80],"a":[82,135,159,194],"dataset":[83],"an":[85,174,210],"unseen":[86],"clinic":[87],"or":[88],"device,":[89],"due":[90],"domain":[92,103,115],"shifts":[93,104],"distribution":[96],"between":[97],"different":[98],"datasets":[99],"across":[100],"clinics.":[101],"Such":[102],"cause":[106],"high":[107],"inter-class":[108],"similarities":[109],"low":[111],"cross-domain":[112,137],"correlations.":[113],"Previous":[114],"generalization":[116,167,212],"are":[118],"often":[119],"susceptible":[120],"under-generalization":[122],"over-generalization,":[124],"especially":[125],"handling":[127],"histopathological":[128,156,203],"images.":[129],"this":[131],"paper,":[132],"we":[133],"propose":[134],"novel":[136],"method":[140,208],"based":[141],"on":[142,199],"multi-granularity":[143],"constraints.":[144],"It":[145],"combines":[146],"pathology-specific":[147],"imaging":[148],"mechanisms":[149],"bound":[151],"generalized":[153],"features":[154],"stable":[160],"representation":[161],"space":[162],"extend":[165],"distance":[168],"as":[169,171],"much":[170],"possible":[172],"under":[173],"adversarial":[175],"constraint":[176],"for":[177],"preventing":[178],"over-generalization.":[179],"effectiveness":[181],"proposed":[184,207],"approach":[185],"against":[186],"state-of-the-art":[188],"has":[190],"been":[191],"demonstrated":[192],"variety":[195],"analysis":[197],"tasks":[198],"four":[200],"independent":[201],"prostate":[202],"imagery":[204],"datasets.":[205],"achieves":[209],"improved":[211],"fine-tuned":[214],"classification":[215],"segmentation":[217],"using":[218],"limited":[219],"samples.":[221]},"counts_by_year":[],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-11-25T00:00:00"}