{"id":"https://openalex.org/W4415428847","doi":"https://doi.org/10.3233/faia250805","title":"A New One-Shot Federated Learning Framework for Medical Imaging Classification with Feature-Guided Rectified Flow and Knowledge Distillation","display_name":"A New One-Shot Federated Learning Framework for Medical Imaging Classification with Feature-Guided Rectified Flow and Knowledge Distillation","publication_year":2025,"publication_date":"2025-10-21","ids":{"openalex":"https://openalex.org/W4415428847","doi":"https://doi.org/10.3233/faia250805"},"language":null,"primary_location":{"id":"doi:10.3233/faia250805","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia250805","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.3233/faia250805","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068840674","display_name":"Yufei Ma","orcid":"https://orcid.org/0000-0002-2670-524X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yufei Ma","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Ultra High Definition Immersive Media Technology, Shenzhen Graduate School, Peking University"],"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Ultra High Definition Immersive Media Technology, Shenzhen Graduate School, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100332172","display_name":"Hanwen Zhang","orcid":"https://orcid.org/0000-0001-7568-5647"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanwen Zhang","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Ultra High Definition Immersive Media Technology, Shenzhen Graduate School, Peking University"],"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Ultra High Definition Immersive Media Technology, Shenzhen Graduate School, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102199653","display_name":"Qiya Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiya Yang","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Ultra High Definition Immersive Media Technology, Shenzhen Graduate School, Peking University"],"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Ultra High Definition Immersive Media Technology, Shenzhen Graduate School, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057015645","display_name":"Guibo Luo","orcid":"https://orcid.org/0000-0002-1709-1207"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guibo Luo","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Ultra High Definition Immersive Media Technology, Shenzhen Graduate School, Peking University"],"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Ultra High Definition Immersive Media Technology, Shenzhen Graduate School, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056706680","display_name":"Yuesheng Zhu","orcid":"https://orcid.org/0000-0003-2524-6800"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuesheng Zhu","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Ultra High Definition Immersive Media Technology, Shenzhen Graduate School, Peking University"],"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Ultra High Definition Immersive Media Technology, Shenzhen Graduate School, Peking University","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5068840674"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":4.8899,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.95807804,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9986000061035156,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9986000061035156,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9524999856948853,"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/T10862","display_name":"AI in cancer detection","score":0.9175999760627747,"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/federated-learning","display_name":"Federated learning","score":0.6452000141143799},{"id":"https://openalex.org/keywords/leakage","display_name":"Leakage (economics)","score":0.4936000108718872},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.49230000376701355},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.42340001463890076},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.41830000281333923},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.41449999809265137},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.40070000290870667},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.400299996137619}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7858999967575073},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.6452000141143799},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5113000273704529},{"id":"https://openalex.org/C2777042071","wikidata":"https://www.wikidata.org/wiki/Q6509304","display_name":"Leakage (economics)","level":2,"score":0.4936000108718872},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.49230000376701355},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44609999656677246},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.42340001463890076},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.41830000281333923},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.41449999809265137},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.40070000290870667},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.400299996137619},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3700000047683716},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3483999967575073},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.3479999899864197},{"id":"https://openalex.org/C489000","wikidata":"https://www.wikidata.org/wiki/Q747385","display_name":"Data flow diagram","level":2,"score":0.31380000710487366},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.30869999527931213},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.30799999833106995},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.26980000734329224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia250805","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia250805","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia250805","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia250805","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"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],"multi-center":[1],"scenarios,":[2],"One-Shot":[3],"Federated":[4],"Learning":[5],"(OSFL)":[6],"has":[7],"attracted":[8],"increasing":[9],"attention":[10],"due":[11],"to":[12,126,165,192],"its":[13],"low":[14,32],"communication":[15],"overhead,":[16],"requiring":[17],"only":[18],"a":[19,47,69,77],"single":[20,48],"round":[21,49],"of":[22,50,137,176],"transmission.":[23],"However,":[24],"existing":[25],"generative":[26,99],"model-based":[27],"OSFL":[28,71],"methods":[29],"suffer":[30],"from":[31],"training":[33],"efficiency":[34],"and":[35,57,84,132,156,168],"potential":[36],"privacy":[37,107,188],"leakage":[38,189],"in":[39,66,75,101],"the":[40,95,122,129,134,170],"healthcare":[41],"domain.":[42],"Additionally,":[43],"achieving":[44,163],"convergence":[45],"within":[46],"model":[51,125],"aggregation":[52,89],"is":[53,73,198],"challenging":[54],"under":[55],"non-Independent":[56],"Identically":[58],"Distributed":[59],"(non-IID)":[60],"data.":[61],"To":[62,116],"address":[63],"these":[64],"challenges,":[65],"this":[67],"paper":[68],"modified":[70],"framework":[72,155],"proposed,":[74],"which":[76],"new":[78,154],"Feature-Guided":[79],"Rectified":[80],"Flow":[81],"Model":[82],"(FG-RF)":[83],"Dual-Layer":[85],"Knowledge":[86],"Distillation":[87],"(DLKD)":[88],"method":[90,157],"are":[91],"developed.":[92],"FG-RF":[93],"on":[94,145],"client":[96],"side":[97],"accelerates":[98],"modeling":[100],"medical":[102,148],"imaging":[103,149],"scenarios":[104],"while":[105],"preserving":[106],"by":[108,173],"synthesizing":[109],"feature-level":[110,183],"images":[111,185],"rather":[112],"than":[113],"pixel-level":[114,193],"images.":[115,195],"handle":[117],"non-IID":[118,147],"distributions,":[119],"DLKD":[120],"enables":[121],"global":[123],"student":[124],"simultaneously":[127],"mimic":[128],"output":[130],"logits":[131],"align":[133],"intermediate-layer":[135],"features":[136],"client-side":[138],"teacher":[139],"models":[140],"during":[141],"aggregation.":[142],"Experimental":[143],"results":[144],"three":[146],"datasets":[150],"show":[151],"that":[152,182],"our":[153,179],"outperform":[158],"multi-round":[159],"federated":[160],"learning":[161],"approaches,":[162],"up":[164],"21.73%":[166],"improvement,":[167],"exceed":[169],"baseline":[171],"FedISCA":[172],"an":[174],"average":[175],"21.75%.":[177],"Furthermore,":[178],"experiments":[180],"demonstrate":[181],"synthetic":[184,194],"significantly":[186],"reduce":[187],"risks":[190],"compared":[191],"The":[196],"code":[197],"available":[199],"at":[200],"https://github.com/LMIAPC/one-shot-fl-medical.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-22T08:09:32.410652","created_date":"2025-10-24T00:00:00"}