{"id":"https://openalex.org/W7138915189","doi":"https://doi.org/10.48550/arxiv.2603.15774","title":"Domain Adaptation Without the Compute Burden for Efficient Whole Slide Image Analysis","display_name":"Domain Adaptation Without the Compute Burden for Efficient Whole Slide Image Analysis","publication_year":2026,"publication_date":"2026-03-16","ids":{"openalex":"https://openalex.org/W7138915189","doi":"https://doi.org/10.48550/arxiv.2603.15774"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.15774","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.15774","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.15774","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054281881","display_name":"Umar Marikkar","orcid":"https://orcid.org/0000-0002-1951-7793"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Marikkar, Umar","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130114972","display_name":"Muhammad Awais","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Awais, Muhammad","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5111136893","display_name":"Sara Atito","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Atito, Sara","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054281881"],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9854999780654907,"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":0.9854999780654907,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.0035000001080334187,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.0017999999690800905,"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/feature","display_name":"Feature (linguistics)","score":0.7253999710083008},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5511999726295471},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5306000113487244},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.515999972820282},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4837000072002411},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.436599999666214},{"id":"https://openalex.org/keywords/feature-detection","display_name":"Feature detection (computer vision)","score":0.42989999055862427},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.4131999909877777},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.41110000014305115}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.763700008392334},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7253999710083008},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6583999991416931},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5511999726295471},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5306000113487244},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.515999972820282},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4837000072002411},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4408999979496002},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.436599999666214},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.42989999055862427},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.4131999909877777},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.41110000014305115},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.3625999987125397},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.36059999465942383},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.3605000078678131},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.35370001196861267},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3467000126838684},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.34459999203681946},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3391000032424927},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.33379998803138733},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3278000056743622},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.31520000100135803},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.313400000333786},{"id":"https://openalex.org/C2779757391","wikidata":"https://www.wikidata.org/wiki/Q6002292","display_name":"Image translation","level":3,"score":0.3005000054836273},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C2776674983","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image editing","level":3,"score":0.2784999907016754},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.2782999873161316},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.267300009727478}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.15774","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.15774","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.15774","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.15774","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Computational":[0],"methods":[1],"on":[2,73,89,141,147],"analyzing":[3],"Whole":[4],"Slide":[5],"Images":[6],"(WSIs)":[7],"enable":[8],"early":[9],"diagnosis":[10],"and":[11,18,101,115,132,154],"treatments":[12],"by":[13],"supporting":[14],"pathologists":[15],"in":[16,119,201,234],"detection":[17],"classification":[19,170,199],"of":[20,27,52,117,129],"tumors.":[21],"However,":[22],"the":[23,108,112,181],"extremely":[24],"high":[25],"resolution":[26],"WSIs":[28],"makes":[29],"end-to-end":[30,139],"training":[31,140],"impractical":[32],"compared":[33],"to":[34,48,82,103,207],"typical":[35],"image":[36,75],"analysis":[37],"tasks.":[38,66,143],"To":[39,110],"address":[40,111],"this,":[41],"most":[42,202],"approaches":[43],"use":[44],"pre-trained":[45,72],"feature":[46,68,95,166,178,194],"extractors":[47,69,167],"obtain":[49],"fixed":[50],"representations":[51],"whole":[53],"slides,":[54],"which":[55,80],"are":[56,70],"then":[57],"combined":[58],"with":[59,164,176,192],"Multiple":[60,133],"Instance":[61,134],"Learning":[62,135],"(MIL)":[63,136],"for":[64,183,224,231],"downstream":[65],"These":[67],"typically":[71],"natural":[74],"datasets":[76],"such":[77],"as":[78],"ImageNet,":[79],"fail":[81,102],"capture":[83,104,208],"domain-specific":[84,87,120],"characteristics.":[85],"Although":[86],"pre-training":[88],"histopathology":[90],"data":[91],"yields":[92,168],"more":[93],"relevant":[94],"representations,":[96],"it":[97,196],"remains":[98],"computationally":[99,221],"expensive":[100],"task-specific":[105,209,232],"characteristics":[106],"within":[107],"domain.":[109],"computational":[113,235],"cost":[114],"lack":[116],"task-specificity":[118],"pre-training,":[121],"we":[122],"propose":[123],"EfficientWSI":[124],"(eWSI),":[125],"a":[126,219,228],"careful":[127],"integration":[128],"Parameter-Efficient-Fine-Tuning":[130],"(PEFT)":[131],"that":[137,160,216],"enables":[138],"WSI":[142,225],"We":[144],"evaluate":[145],"eWSI":[146,161,189,217],"seven":[148],"WSI-level":[149],"tasks":[150],"over":[151],"Camelyon16,":[152],"TCGA":[153],"BRACS":[155],"datasets.":[156],"Our":[157,213],"results":[158],"show":[159],"when":[162,188],"applied":[163,191],"ImageNet":[165],"strong":[169],"performance,":[171],"matching":[172],"or":[173],"outperforming":[174],"MILs":[175],"in-domain":[177,185,193],"extractors,":[179,195],"alleviating":[180],"need":[182],"extensive":[184],"pre-training.":[186],"Furthermore,":[187],"is":[190],"further":[197],"improves":[198],"performance":[200],"cases,":[203],"demonstrating":[204],"its":[205],"ability":[206],"information":[210],"where":[211],"beneficial.":[212],"findings":[214],"suggest":[215],"provides":[218],"task-targeted,":[220],"efficient":[222],"path":[223],"tasks,":[226],"offering":[227],"promising":[229],"direction":[230],"learning":[233],"pathology.":[236]},"counts_by_year":[],"updated_date":"2026-03-20T20:54:20.808490","created_date":"2026-03-20T00:00:00"}