{"id":"https://openalex.org/W7127372335","doi":"https://doi.org/10.3390/make8020034","title":"AuraViT-FL: A Resource-Efficient 2D Hybrid Transformer Framework for Federated Lung Tumor Segmentation","display_name":"AuraViT-FL: A Resource-Efficient 2D Hybrid Transformer Framework for Federated Lung Tumor Segmentation","publication_year":2026,"publication_date":"2026-02-03","ids":{"openalex":"https://openalex.org/W7127372335","doi":"https://doi.org/10.3390/make8020034"},"language":"en","primary_location":{"id":"doi:10.3390/make8020034","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make8020034","pdf_url":"https://www.mdpi.com/2504-4990/8/2/34/pdf","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-4990/8/2/34/pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124932843","display_name":"Mohamed A. Abdelhamed","orcid":null},"institutions":[{"id":"https://openalex.org/I57629906","display_name":"Nile University","ror":"https://ror.org/03cg7cp61","country_code":"EG","type":"education","lineage":["https://openalex.org/I57629906"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Mohamed A. Abdelhamed","raw_affiliation_strings":["School of Engineering and Applied Sciences, Nile University, Giza 12588, Egypt"],"raw_orcid":"https://orcid.org/0009-0000-1330-292X","affiliations":[{"raw_affiliation_string":"School of Engineering and Applied Sciences, Nile University, Giza 12588, Egypt","institution_ids":["https://openalex.org/I57629906"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117140972","display_name":"Hana Mohammed Nassef","orcid":null},"institutions":[{"id":"https://openalex.org/I57629906","display_name":"Nile University","ror":"https://ror.org/03cg7cp61","country_code":"EG","type":"education","lineage":["https://openalex.org/I57629906"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Hana M. Nassef","raw_affiliation_strings":["School of Engineering and Applied Sciences, Nile University, Giza 12588, Egypt"],"raw_orcid":"https://orcid.org/0009-0001-3016-3893","affiliations":[{"raw_affiliation_string":"School of Engineering and Applied Sciences, Nile University, Giza 12588, Egypt","institution_ids":["https://openalex.org/I57629906"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093641345","display_name":"sara. abdelnasser","orcid":null},"institutions":[{"id":"https://openalex.org/I57629906","display_name":"Nile University","ror":"https://ror.org/03cg7cp61","country_code":"EG","type":"education","lineage":["https://openalex.org/I57629906"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Sara Abdelnasser","raw_affiliation_strings":["School of Engineering and Applied Sciences, Nile University, Giza 12588, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering and Applied Sciences, Nile University, Giza 12588, Egypt","institution_ids":["https://openalex.org/I57629906"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080442213","display_name":"Sahar Selim","orcid":"https://orcid.org/0000-0002-9886-1364"},"institutions":[{"id":"https://openalex.org/I57629906","display_name":"Nile University","ror":"https://ror.org/03cg7cp61","country_code":"EG","type":"education","lineage":["https://openalex.org/I57629906"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Sahar Selim","raw_affiliation_strings":["Center for Informatics Science (CIS), School of Information Technology and Computer Science, Nile University, Giza 12588, Egypt"],"raw_orcid":"https://orcid.org/0000-0002-9886-1364","affiliations":[{"raw_affiliation_string":"Center for Informatics Science (CIS), School of Information Technology and Computer Science, Nile University, Giza 12588, Egypt","institution_ids":["https://openalex.org/I57629906"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083130551","display_name":"Lobna A. Said","orcid":"https://orcid.org/0000-0001-8223-4625"},"institutions":[{"id":"https://openalex.org/I57629906","display_name":"Nile University","ror":"https://ror.org/03cg7cp61","country_code":"EG","type":"education","lineage":["https://openalex.org/I57629906"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Lobna A. Said","raw_affiliation_strings":["Nanoelectronics Integrated Systems Center (NISC), Nile University, Giza 12588, Egypt"],"raw_orcid":"https://orcid.org/0000-0001-8223-4625","affiliations":[{"raw_affiliation_string":"Nanoelectronics Integrated Systems Center (NISC), Nile University, Giza 12588, Egypt","institution_ids":["https://openalex.org/I57629906"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I57629906"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":9.2055,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.94473656,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"8","issue":"2","first_page":"34","last_page":"34"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.6326000094413757,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.6326000094413757,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory 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/T10036","display_name":"Advanced Neural Network Applications","score":0.10779999941587448,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10358","display_name":"Advanced Radiotherapy Techniques","score":0.0892999991774559,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6327000260353088},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.5899999737739563},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4207000136375427},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.37940001487731934},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.33880001306533813},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.33739998936653137},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3359000086784363},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.33570000529289246}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7889000177383423},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6327000260353088},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.5899999737739563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5799999833106995},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.436599999666214},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4207000136375427},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3912000060081482},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.37940001487731934},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.33880001306533813},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.33739998936653137},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.33570000529289246},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.32339999079704285},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.32030001282691956},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3192000091075897},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.310699999332428},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.3095000088214874},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.29820001125335693},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2919999957084656},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2777000069618225},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.2757999897003174},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.26030001044273376}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/make8020034","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make8020034","pdf_url":"https://www.mdpi.com/2504-4990/8/2/34/pdf","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6af075afc5cb45b7bc464d9dbc9b85fd","is_oa":false,"landing_page_url":"https://doaj.org/article/6af075afc5cb45b7bc464d9dbc9b85fd","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning and Knowledge Extraction, Vol 8, Iss 2, p 34 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/make8020034","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make8020034","pdf_url":"https://www.mdpi.com/2504-4990/8/2/34/pdf","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320319010","display_name":"Arab-German Young Academy of Sciences and Humanities","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7127372335.pdf","grobid_xml":"https://content.openalex.org/works/W7127372335.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2010781518","https://openalex.org/W2138711374","https://openalex.org/W2801958465","https://openalex.org/W2896246551","https://openalex.org/W2936495845","https://openalex.org/W2980848734","https://openalex.org/W2999370362","https://openalex.org/W3014974815","https://openalex.org/W3160694286","https://openalex.org/W3172681723","https://openalex.org/W3182134206","https://openalex.org/W4206706211","https://openalex.org/W4212875960","https://openalex.org/W4287225920","https://openalex.org/W4362603432","https://openalex.org/W4385210255","https://openalex.org/W4389240763","https://openalex.org/W4391109864","https://openalex.org/W4400881081","https://openalex.org/W4401657815","https://openalex.org/W4403503010","https://openalex.org/W4405701133","https://openalex.org/W4408958047","https://openalex.org/W4409473984","https://openalex.org/W4409930463","https://openalex.org/W4415812903"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"lung":[1,47],"tumor":[2,13,48],"segmentation":[3,49],"using":[4],"computed":[5],"tomography":[6],"(CT)":[7],"scans":[8],"is":[9,22,114,166],"needed":[10],"for":[11,105],"efficient":[12],"treatment.":[14],"However,":[15],"the":[16,62,67,92,182,201,213],"development":[17],"of":[18,191],"deep":[19],"learning":[20,129,145],"models":[21,50],"often":[23],"constrained":[24],"by":[25,223],"strict":[26],"patient":[27,56,138],"privacy":[28],"regulations":[29],"that":[30,40,76,131,181],"limit":[31],"direct":[32],"data":[33,160],"sharing.":[34],"This":[35],"work":[36],"presents":[37],"a":[38,78,125,143,153,186,205],"system":[39,162],"enables":[41],"multi-institutional":[42],"collaboration":[43,133],"while":[44,136,193,226],"training":[45],"high-quality":[46],"without":[51],"requiring":[52],"access":[53],"to":[54,158,197],"sensitive":[55],"data.":[57],"The":[58,140,164,178],"proposed":[59],"framework":[60,141,165],"features":[61],"AuraViT":[63,94],"suite,":[64],"which":[65],"includes":[66],"standard":[68,183],"AuraViT\u2014a":[69],"hybrid":[70],"model":[71,173,221],"with":[72,147,216],"136":[73],"million":[74],"parameters":[75,219],"combines":[77],"Vision":[79],"Transformer":[80],"(ViT)":[81],"encoder,":[82],"Atrous":[83],"Spatial":[84],"Pyramid":[85],"Pooling":[86],"(ASPP),":[87],"and":[88,99,108,122,152,161,175,210],"attention-gated":[89],"residual":[90],"connections\u2014and":[91],"Lightweight":[93],"(LAURA)":[95],"family":[96],"(Small,":[97],"Tiny,":[98],"Mobile).":[100],"These":[101],"variants":[102],"are":[103],"designed":[104],"resource-constrained":[106],"environments":[107],"potential":[109],"edge":[110],"deployment":[111],"scenarios.":[112],"Training":[113],"conducted":[115],"on":[116,172,232],"publicly":[117],"available":[118],"datasets":[119],"(MSD":[120],"Lung":[121],"NSCLC)":[123],"in":[124],"simulated":[126],"five-client":[127],"federated":[128,144],"setup":[130,146],"emulates":[132],"among":[134],"institutions":[135],"ensuring":[137],"privacy.":[139],"uses":[142],"FedProx,":[148],"adaptive":[149],"weighted":[150],"aggregation,":[151],"dynamic":[154],"virtual":[155],"client":[156],"strategy":[157],"handle":[159],"differences.":[163],"further":[167],"evaluated":[168],"through":[169],"ablation":[170],"studies":[171],"architecture":[174],"feature":[176],"importance.":[177],"results":[179],"show":[180,204],"AuraViT-FL":[184],"achieves":[185],"global":[187],"mean":[188],"Dice":[189,231],"score":[190],"80.81%,":[192],"maintaining":[194,227],"performance":[195,229],"close":[196],"centralized":[198],"training.":[199],"Additionally,":[200],"LAURA":[202],"variations":[203],"better":[206],"trade-off":[207],"between":[208],"accuracy":[209],"efficiency.":[211],"Notably,":[212],"Mobile":[214],"variant":[215],"\u223c5":[217],"M":[218],"reduces":[220],"complexity":[222],"over":[224],"96%":[225],"competitive":[228],"(82.96%":[230],"MSD":[233],"Lung).":[234]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-15T08:34:33.830935","created_date":"2026-02-04T00:00:00"}