{"id":"https://openalex.org/W4400406704","doi":"https://doi.org/10.1007/s11263-024-02158-9","title":"Infproto-Powered Adaptive Classifier and Agnostic Feature Learning for Single Domain Generalization in Medical Images","display_name":"Infproto-Powered Adaptive Classifier and Agnostic Feature Learning for Single Domain Generalization in Medical Images","publication_year":2024,"publication_date":"2024-07-08","ids":{"openalex":"https://openalex.org/W4400406704","doi":"https://doi.org/10.1007/s11263-024-02158-9"},"language":"en","primary_location":{"id":"doi:10.1007/s11263-024-02158-9","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s11263-024-02158-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11263-024-02158-9.pdf","source":{"id":"https://openalex.org/S25538012","display_name":"International Journal of Computer Vision","issn_l":"0920-5691","issn":["0920-5691","1573-1405"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Vision","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11263-024-02158-9.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059247334","display_name":"Xiaoqing Guo","orcid":"https://orcid.org/0000-0002-9476-521X"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]},{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]},{"id":"https://openalex.org/I4210146410","display_name":"Science Oxford","ror":"https://ror.org/04j8yhy50","country_code":"GB","type":"nonprofit","lineage":["https://openalex.org/I4210146410"]}],"countries":["GB","HK"],"is_corresponding":false,"raw_author_name":"Xiaoqing Guo","raw_affiliation_strings":["Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China","Department of Engineering Science, University of Oxford, Oxford, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0002-9476-521X","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]},{"raw_affiliation_string":"Department of Engineering Science, University of Oxford, Oxford, United Kingdom","institution_ids":["https://openalex.org/I4210146410","https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041019033","display_name":"Jie Liu","orcid":"https://orcid.org/0000-0002-1327-1315"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jie Liu","raw_affiliation_strings":["Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073968803","display_name":"Yixuan Yuan","orcid":"https://orcid.org/0000-0002-0853-6948"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]},{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Yixuan Yuan","raw_affiliation_strings":["Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China","Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]},{"raw_affiliation_string":"Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5073968803"],"corresponding_institution_ids":["https://openalex.org/I168719708","https://openalex.org/I177725633"],"apc_list":{"value":2890,"currency":"EUR","value_usd":3690},"apc_paid":{"value":2890,"currency":"EUR","value_usd":3690},"fwci":0.2778,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.59785968,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"132","issue":"12","first_page":"5905","last_page":"5928"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9983999729156494,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9983999729156494,"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":0.9833999872207642,"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/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9818999767303467,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"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"}}],"keywords":[{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.8103969097137451},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6961166858673096},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6296847462654114},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.628876268863678},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5777210593223572},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4938569664955139},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4425264000892639},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3897261619567871},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3413819670677185}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.8103969097137451},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6961166858673096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6296847462654114},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.628876268863678},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5777210593223572},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4938569664955139},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4425264000892639},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3897261619567871},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3413819670677185}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s11263-024-02158-9","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s11263-024-02158-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11263-024-02158-9.pdf","source":{"id":"https://openalex.org/S25538012","display_name":"International Journal of Computer Vision","issn_l":"0920-5691","issn":["0920-5691","1573-1405"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Vision","raw_type":"journal-article"},{"id":"pmh:oai:ora.ox.ac.uk:uuid:e97c39f9-9302-48f7-90e2-902b7a0aa8b4","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402636","display_name":"Oxford University Research Archive (ORA) (University of Oxford)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40120149","host_organization_name":"University of Oxford","host_organization_lineage":["https://openalex.org/I40120149"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Jisc Publications Router","raw_type":"Journal article"},{"id":"pmh:oai:pure.atira.dk:publications/f631f2d8-d036-497e-8cc9-0fdee8b6fe98","is_oa":true,"landing_page_url":"https://hdl.handle.net/2031/f631f2d8-d036-497e-8cc9-0fdee8b6fe98","pdf_url":null,"source":{"id":"https://openalex.org/S7407055387","display_name":"CityU Scholars","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Guo, X, Liu, J & Yuan, Y 2024, 'Infproto-powered Adaptive Classifier and Agnostic Feature Learning for Single Domain Generalization in Medical Images', International Journal of Computer Vision, vol. 132, no. 12, pp. 5905\u20135928. https://doi.org/10.1007/s11263-024-02158-9","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s11263-024-02158-9","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s11263-024-02158-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11263-024-02158-9.pdf","source":{"id":"https://openalex.org/S25538012","display_name":"International Journal of Computer Vision","issn_l":"0920-5691","issn":["0920-5691","1573-1405"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Vision","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4400406704.pdf"},"referenced_works_count":69,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2021088830","https://openalex.org/W2412782625","https://openalex.org/W2560023338","https://openalex.org/W2560328367","https://openalex.org/W2736981815","https://openalex.org/W2806187986","https://openalex.org/W2963741402","https://openalex.org/W2963983207","https://openalex.org/W2964309882","https://openalex.org/W2981488580","https://openalex.org/W2990019157","https://openalex.org/W2993235622","https://openalex.org/W2996290406","https://openalex.org/W2996495478","https://openalex.org/W3006326483","https://openalex.org/W3014641072","https://openalex.org/W3014974815","https://openalex.org/W3034203264","https://openalex.org/W3034373371","https://openalex.org/W3034373787","https://openalex.org/W3035236545","https://openalex.org/W3045441084","https://openalex.org/W3089931213","https://openalex.org/W3090492687","https://openalex.org/W3092344722","https://openalex.org/W3092500685","https://openalex.org/W3092753908","https://openalex.org/W3100350094","https://openalex.org/W3106906018","https://openalex.org/W3108189450","https://openalex.org/W3112701542","https://openalex.org/W3113148327","https://openalex.org/W3114304902","https://openalex.org/W3120333390","https://openalex.org/W3136481290","https://openalex.org/W3169545167","https://openalex.org/W3172292202","https://openalex.org/W3172854222","https://openalex.org/W3173251459","https://openalex.org/W3175042385","https://openalex.org/W3175685622","https://openalex.org/W3175956495","https://openalex.org/W3176065502","https://openalex.org/W3177182473","https://openalex.org/W3179539006","https://openalex.org/W3180439858","https://openalex.org/W3183864931","https://openalex.org/W3189999308","https://openalex.org/W3199141325","https://openalex.org/W3199502724","https://openalex.org/W3200027277","https://openalex.org/W3201774370","https://openalex.org/W3202263958","https://openalex.org/W3202641951","https://openalex.org/W3203033840","https://openalex.org/W3205301720","https://openalex.org/W3206154535","https://openalex.org/W3214910576","https://openalex.org/W3216869756","https://openalex.org/W4211022174","https://openalex.org/W4213335251","https://openalex.org/W4229723800","https://openalex.org/W4297792979","https://openalex.org/W4382467366","https://openalex.org/W4386065590","https://openalex.org/W6772750526","https://openalex.org/W6781630272","https://openalex.org/W6791853581"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W1482209366","https://openalex.org/W2110523656","https://openalex.org/W2521627374","https://openalex.org/W1487808658"],"abstract_inverted_index":{"Abstract":[0],"Designing":[1],"a":[2,98,118,167],"single":[3,55],"domain":[4,13,30,35,165,170],"generalization":[5],"(DG)":[6],"framework":[7],"that":[8,43],"generalizes":[9],"from":[10,134],"one":[11],"source":[12,34,164,169,206],"to":[14,28,66,84,102,122,150,189,211],"arbitrary":[15],"unseen":[16,151],"domains":[17],"is":[18,166],"practical":[19],"yet":[20],"challenging":[21],"in":[22,54,109,162,218,259],"medical":[23],"image":[24],"segmentation,":[25],"mainly":[26],"due":[27],"the":[29,68,71,86,105,110,124,135,142,163,193,209,229,243],"shift":[31],"and":[32,47,57,78,96,137,144,171,186,238,257,263],"limited":[33],"information.":[36],"To":[37,153],"tackle":[38],"these":[39],"issues,":[40],"we":[41,116,158],"reason":[42],"domain-adaptive":[44,120,146,195],"classifier":[45,87,121,130],"learning":[46,69],"domain-agnostic":[48,155],"feature":[49],"extraction":[50],"are":[51],"key":[52],"components":[53],"DG,":[56],"further":[58],"propose":[59],"an":[60],"adaptive":[61],"infinite":[62,106,179,183],"prototypes":[63,83,133],"(InfProto)":[64],"scheme":[65],"facilitate":[67],"of":[70,112,192,214,231,245,255],"two":[72],"components.":[73],"InfProto":[74],"harnesses":[75],"high-order":[76],"statistics":[77],"infinitely":[79,131],"samples":[80,132],"class-conditional":[81],"instance-specific":[82],"form":[85],"for":[88,126],"discriminability":[89],"enhancement.":[90],"We":[91],"then":[92,172],"introduce":[93],"probabilistic":[94],"modeling":[95],"provide":[97],"theoretic":[99],"upper":[100],"bound":[101],"implicitly":[103],"perform":[104],"prototype":[107,180,184],"sampling":[108],"optimization":[111],"InfProto.":[113],"Incorporating":[114],"InfProto,":[115],"design":[117],"hierarchical":[119,194],"elasticize":[123],"model":[125,210],"varying":[127],"domains.":[128,152],"This":[129],"instance":[136,161],"mini-batch":[138],"data":[139],"distributions,":[140],"forming":[141],"instance-level":[143,178],"mini-batch-level":[145],"classifiers,":[147],"thereby":[148],"generalizing":[149],"extract":[154],"features":[156],",":[157],"assume":[159],"each":[160,246],"micro":[168,205],"devise":[173],"three":[174,198],"complementary":[175,199],"strategies,":[176],"i.e.,":[177],"exchange,":[181],"instance-batch":[182],"interaction,":[185],"consistency":[187],"regularization,":[188],"constrain":[190],"outputs":[191],"classifier.":[196],"These":[197],"strategies":[200],"minimize":[201],"distribution":[202],"shifts":[203],"among":[204],"domains,":[207],"enabling":[208],"get":[212],"rid":[213],"domain-specific":[215],"characterizations":[216],"and,":[217],"turn,":[219],"concentrating":[220],"on":[221,261],"semantically":[222],"discriminative":[223],"features.":[224],"Extensive":[225],"comparison":[226],"experiments":[227],"demonstrate":[228],"superiority":[230],"our":[232,250],"approach":[233],"compared":[234],"with":[235],"state-of-the-art":[236],"counterparts,":[237],"comprehensive":[239],"ablation":[240],"studies":[241],"verify":[242],"effect":[244],"proposed":[247],"component.":[248],"Notably,":[249],"method":[251],"exhibits":[252],"average":[253],"improvements":[254],"15.568%":[256],"17.429%":[258],"dice":[260],"polyp":[262],"surgical":[264],"instrument":[265],"segmentation":[266],"benchmarks.":[267]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}