{"id":"https://openalex.org/W7162813316","doi":"https://doi.org/10.48550/arxiv.2605.29122","title":"Robust Cross-Domain Generalization Using Unlabeled Target Data with Source-Domain Supervision","display_name":"Robust Cross-Domain Generalization Using Unlabeled Target Data with Source-Domain Supervision","publication_year":2026,"publication_date":"2026-05-27","ids":{"openalex":"https://openalex.org/W7162813316","doi":"https://doi.org/10.48550/arxiv.2605.29122"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.29122","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29122","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":null,"license_id":null,"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.2605.29122","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020142976","display_name":"Yuyue Zhou","orcid":"https://orcid.org/0000-0003-3606-3401"},"institutions":[{"id":"https://openalex.org/I3130081645","display_name":"Yangon University of Economics","ror":"https://ror.org/0133h5567","country_code":"MM","type":"education","lineage":["https://openalex.org/I3130081645"]},{"id":"https://openalex.org/I4210157723","display_name":"Yueyang Changling Equipment Research Institute (China)","ror":"https://ror.org/04yq0fn97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210157723"]}],"countries":["CN","MM"],"is_corresponding":false,"raw_author_name":"Zhou, Yuyue","raw_affiliation_strings":["Kai Yue"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kai Yue","institution_ids":["https://openalex.org/I3130081645","https://openalex.org/I4210157723"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029876399","display_name":"Shrimanti Ghosh","orcid":"https://orcid.org/0000-0003-0659-0147"},"institutions":[{"id":"https://openalex.org/I3130081645","display_name":"Yangon University of Economics","ror":"https://ror.org/0133h5567","country_code":"MM","type":"education","lineage":["https://openalex.org/I3130081645"]},{"id":"https://openalex.org/I4210157723","display_name":"Yueyang Changling Equipment Research Institute (China)","ror":"https://ror.org/04yq0fn97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210157723"]}],"countries":["CN","MM"],"is_corresponding":false,"raw_author_name":"Ghosh, Shrimanti","raw_affiliation_strings":["Kai Yue"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kai Yue","institution_ids":["https://openalex.org/I3130081645","https://openalex.org/I4210157723"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137393924","display_name":"Michael","orcid":null},"institutions":[{"id":"https://openalex.org/I3130081645","display_name":"Yangon University of Economics","ror":"https://ror.org/0133h5567","country_code":"MM","type":"education","lineage":["https://openalex.org/I3130081645"]},{"id":"https://openalex.org/I4210157723","display_name":"Yueyang Changling Equipment Research Institute (China)","ror":"https://ror.org/04yq0fn97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210157723"]}],"countries":["CN","MM"],"is_corresponding":false,"raw_author_name":"Michael","raw_affiliation_strings":["Kai Yue"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kai Yue","institution_ids":["https://openalex.org/I3130081645","https://openalex.org/I4210157723"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137330091","display_name":"Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136608368","display_name":"Justin JY Kim","orcid":"https://orcid.org/0009-0009-7769-4147"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Justin JY","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039110200","display_name":"Jessica Knight","orcid":"https://orcid.org/0000-0003-2508-6130"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Knight, Jessica","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133242915","display_name":"Steel McDonald","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"McDonald, Steel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137314645","display_name":"Vincent Man","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Man, Vincent","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137376253","display_name":"Jacob L. Jaremko","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jaremko, Jacob L.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137385434","display_name":"Abhilash Hareendranathan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hareendranathan, Abhilash","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":10,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.4097999930381775,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.4097999930381775,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/T11738","display_name":"Ultrasound in Clinical Applications","score":0.2590000033378601,"subfield":{"id":"https://openalex.org/subfields/2706","display_name":"Critical Care and Intensive Care Medicine"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0885000005364418,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5900999903678894},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.531000018119812},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5214999914169312},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5041000247001648},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.4666000008583069},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.4413999915122986},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3939000070095062},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.39089998602867126},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.37310001254081726}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.739300012588501},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7050999999046326},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5900999903678894},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.531000018119812},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5214999914169312},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5041000247001648},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.4666000008583069},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.4413999915122986},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40459999442100525},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3939000070095062},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.39089998602867126},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.37310001254081726},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.36649999022483826},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.3407999873161316},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33739998936653137},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.33149999380111694},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.32280001044273376},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.3037000000476837},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30149999260902405},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3009999990463257},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.296999990940094},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.29580000042915344},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.2831999957561493},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.2784999907016754},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2754000127315521},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2572999894618988},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.29122","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29122","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.29122","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29122","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"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":{"It":[0],"is":[1,31,97],"often":[2,32,68],"desirable":[3],"to":[4,14,77,100,131,144,195,243],"generalize":[5],"medical":[6],"imaging":[7],"AI":[8,60],"models":[9,27,81],"trained":[10],"with":[11,28,152,165],"dense":[12,158],"annotations":[13,30],"data":[15,85,105,187],"acquired":[16,164],"from":[17,86,201],"different":[18],"ultrasound":[19,47,234],"scanners":[20],"or":[21,89,246],"clinical":[22],"sites;":[23],"however,":[24],"retraining":[25],"these":[26],"new":[29],"difficult":[33],"and":[34,53,91,104,117,128,138,191,229],"costly.":[35],"We":[36],"examine":[37],"this":[38,206],"challenge":[39],"in":[40],"pediatric":[41,203],"wrist":[42],"fracture":[43,66],"assessment":[44],"using":[45],"point-of-care":[46],"(POCUS),":[48],"where":[49],"fractures":[50],"are":[51],"common":[52],"can":[54,240],"be":[55,241],"effectively":[56],"triaged":[57],"via":[58],"ultrasound.":[59],"has":[61],"shown":[62],"radiologist-level":[63],"performance":[64],"for":[65,188,232],"detection,":[67],"aided":[69],"by":[70],"high-quality":[71],"bony":[72],"structure":[73],"segmentation.":[74],"However,":[75],"due":[76,99],"significant":[78],"domain":[79,220],"shifts,":[80],"perform":[82],"poorly":[83],"on":[84,217],"other":[87],"centers":[88],"probes,":[90],"obtaining":[92],"segmentation":[93],"labels":[94],"across":[95],"devices":[96],"impractical":[98],"manual":[101],"annotation":[102],"effort":[103],"privacy":[106],"concerns.":[107],"To":[108],"address":[109],"this,":[110],"we":[111],"propose":[112],"a":[113,140,153,166,227,237],"target-informed":[114],"self-supervised":[115],"pretraining":[116,194],"model-ensemble":[118],"strategy.":[119],"Specifically,":[120],"our":[121],"approach":[122,207,231],"combines":[123],"masked":[124],"image":[125],"modeling":[126],"(MIM)":[127],"contrastive":[129],"learning":[130,248],"learn":[132],"target-domain":[133,193],"structural":[134],"representations":[135],"without":[136],"labels,":[137,159],"introduces":[139],"confidence-aware":[141],"infusion":[142],"head":[143],"adaptively":[145],"integrate":[146],"predictions.":[147],"The":[148,172],"source":[149,186],"dataset,":[150,163],"collected":[151],"Philips":[154],"Lumify":[155],"probe,":[156,169],"contained":[157],"while":[160],"the":[161,179,218,222],"target":[162,219],"TeleMED":[167],"portable":[168],"was":[170],"unlabeled.":[171],"datasets":[173],"were":[174],"kept":[175],"strictly":[176],"separate":[177],"throughout":[178],"entire":[180],"process.":[181],"Our":[182],"method":[183],"used":[184],"labeled":[185],"supervised":[189],"training":[190],"leveraged":[192],"improve":[196],"generalization.":[197],"On":[198],"318":[199],"images":[200],"62":[202],"POCUS":[204],"videos,":[205],"significantly":[208],"improved":[209],"cross-device":[210],"performance,":[211],"achieving":[212],"over":[213],"6%":[214],"Dice":[215],"improvement":[216],"versus":[221],"baseline.":[223],"These":[224],"results":[225],"demonstrate":[226],"label-efficient":[228],"privacy-preserving":[230],"cross-device-robust":[233],"AI,":[235],"offering":[236],"framework":[238],"that":[239],"extended":[242],"multi-center":[244],"studies":[245],"federated":[247],"setups.":[249]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-30T00:00:00"}