{"id":"https://openalex.org/W7139138637","doi":"https://doi.org/10.1109/globecom59602.2025.11431877","title":"FedU-KAN: Cloud-Enhanced Privacy-Preserving Federated Learning for Medical Image Segmentation Based on U-KAN","display_name":"FedU-KAN: Cloud-Enhanced Privacy-Preserving Federated Learning for Medical Image Segmentation Based on U-KAN","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W7139138637","doi":"https://doi.org/10.1109/globecom59602.2025.11431877"},"language":null,"primary_location":{"id":"doi:10.1109/globecom59602.2025.11431877","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11431877","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100384078","display_name":"Yingjie Liu","orcid":"https://orcid.org/0000-0001-5391-7996"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingjie Liu","raw_affiliation_strings":["China University of Mining and Technology,The Department of Computer Science,Xuzhou,China,221116"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Mining and Technology,The Department of Computer Science,Xuzhou,China,221116","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129881711","display_name":"Haotian Chi","orcid":null},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haotian Chi","raw_affiliation_strings":["Shanxi University,School of Computer and Information Technology,Taiyuan,China,030006"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanxi University,School of Computer and Information Technology,Taiyuan,China,030006","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107909020","display_name":"Yonggang Li","orcid":"https://orcid.org/0009-0003-7751-697X"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonggang Li","raw_affiliation_strings":["China University of Mining and Technology,The Department of Computer Science,Xuzhou,China,221116"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Mining and Technology,The Department of Computer Science,Xuzhou,China,221116","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124752305","display_name":"Yuwei Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuwei Wang","raw_affiliation_strings":["Shanxi University,School of Computer and Information Technology,Taiyuan,China,030006"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanxi University,School of Computer and Information Technology,Taiyuan,China,030006","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027335042","display_name":"Shunrong Jiang","orcid":"https://orcid.org/0000-0003-2823-1794"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shunrong Jiang","raw_affiliation_strings":["China University of Mining and Technology,The Department of Computer Science,Xuzhou,China,221116"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Mining and Technology,The Department of Computer Science,Xuzhou,China,221116","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060514022","display_name":"Xiaojiang Du","orcid":"https://orcid.org/0000-0003-4235-9671"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaojiang Du","raw_affiliation_strings":["Stevens Institute of Technology,Department of Electrical and Computer Engineering,Hoboken,NJ,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stevens Institute of Technology,Department of Electrical and Computer Engineering,Hoboken,NJ,USA","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072015888","display_name":"Nadjib Aitsaadi","orcid":"https://orcid.org/0009-0007-8538-8380"},"institutions":[{"id":"https://openalex.org/I195731000","display_name":"Universit\u00e9 de Versailles Saint-Quentin-en-Yvelines","ror":"https://ror.org/03mkjjy25","country_code":"FR","type":"education","lineage":["https://openalex.org/I195731000","https://openalex.org/I277688954"]},{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Nadjib AitSaadi","raw_affiliation_strings":["Universit&#x00E9; Paris-Saclay, UVSQ, DAVID,France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit&#x00E9; Paris-Saclay, UVSQ, DAVID,France","institution_ids":["https://openalex.org/I195731000","https://openalex.org/I277688954"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"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":"1841","last_page":"1846"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9086999893188477,"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":0.9086999893188477,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.007899999618530273,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.006300000008195639,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.7168999910354614},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6952999830245972},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5393999814987183},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.5221999883651733},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5058000087738037},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.4722000062465668},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4575999975204468},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.3878999948501587}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8234999775886536},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.7168999910354614},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6952999830245972},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5393999814987183},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.5221999883651733},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5058000087738037},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48899999260902405},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.4722000062465668},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4575999975204468},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.3878999948501587},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3815000057220459},{"id":"https://openalex.org/C2776848632","wikidata":"https://www.wikidata.org/wiki/Q853463","display_name":"Clipping (morphology)","level":2,"score":0.37630000710487366},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35359999537467957},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32839998602867126},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2935999929904938},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C2779965156","wikidata":"https://www.wikidata.org/wiki/Q5227350","display_name":"Data sharing","level":3,"score":0.2766999900341034},{"id":"https://openalex.org/C3017597292","wikidata":"https://www.wikidata.org/wiki/Q25052250","display_name":"Privacy protection","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.2621999979019165},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.260699987411499}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom59602.2025.11431877","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11431877","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.45205679535865784,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2122558727","https://openalex.org/W2125492197","https://openalex.org/W2620234603","https://openalex.org/W2884436604","https://openalex.org/W2997286550","https://openalex.org/W4386066535","https://openalex.org/W4392397365","https://openalex.org/W4401571602","https://openalex.org/W4409367393"],"related_works":[],"abstract_inverted_index":{"Machine":[0],"learning":[1,30],"is":[2],"gradually":[3],"transforming":[4],"medical":[5,15,90,161],"image":[6,91],"segmentation.":[7],"However,":[8],"its":[9,56],"accuracy":[10],"often":[11],"relies":[12],"on":[13,69,108,127],"large-scale":[14],"datasets,":[16,132],"while":[17,117],"centralized":[18],"data":[19],"collection":[20],"raises":[21],"serious":[22],"privacy":[23,100,122,154],"concerns.":[24],"To":[25,72],"address":[26],"this":[27,46,74],"issue,":[28],"federated":[29,89],"(FL)":[31],"enables":[32],"collaborative":[33],"model":[34,157],"training":[35,68],"without":[36],"sharing":[37],"raw":[38],"data,":[39],"thus":[40],"effectively":[41,152],"protecting":[42],"patient":[43],"privacy.":[44],"Despite":[45],"advantage,":[47],"commonly":[48],"used":[49],"segmentation":[50,92,162],"models,":[51],"such":[52],"as":[53],"U-Net":[54],"and":[55,130,140,156],"variants,":[57],"typically":[58],"have":[59],"large":[60],"parameter":[61],"sizes,":[62],"making":[63],"them":[64],"inefficient":[65],"for":[66,88],"local":[67],"FL":[70,144],"clients.":[71],"overcome":[73],"challenge,":[75],"we":[76,95],"propose":[77],"FedU-KAN,":[78],"a":[79],"framework":[80],"built":[81],"upon":[82],"the":[83,119,128],"lightweight":[84],"U-KAN":[85],"architecture,":[86],"tailored":[87],"tasks.":[93],"Moreover,":[94],"design":[96],"an":[97],"adaptive":[98],"differential":[99],"mechanism":[101],"that":[102,149],"dynamically":[103],"adjusts":[104],"gradient":[105],"clipping":[106],"based":[107],"feature":[109],"importance.":[110],"This":[111],"approach":[112],"helps":[113],"preserve":[114],"anatomical":[115],"details":[116],"reducing":[118],"risk":[120],"of":[121,138],"leakage.":[123],"We":[124],"evaluate":[125],"FedU-KAN":[126,150],"CVC-ClinicDB":[129],"Kvasir-SEG":[131],"where":[133],"it":[134],"achieves":[135],"IoU":[136],"scores":[137],"87.09%":[139],"83.38%,":[141],"respectively\u2014outperforming":[142],"standard":[143],"baselines.":[145],"These":[146],"results":[147],"demonstrate":[148],"can":[151],"balance":[153],"protection":[155],"performance":[158],"in":[159],"real-world":[160],"scenarios.":[163]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-20T00:00:00"}
