{"id":"https://openalex.org/W4321010562","doi":"https://doi.org/10.48550/arxiv.2302.06352","title":"Deep Anatomical Federated Network (Dafne): An open client-server framework for the continuous, collaborative improvement of deep learning-based medical image segmentation","display_name":"Deep Anatomical Federated Network (Dafne): An open client-server framework for the continuous, collaborative improvement of deep learning-based medical image segmentation","publication_year":2023,"publication_date":"2023-02-13","ids":{"openalex":"https://openalex.org/W4321010562","doi":"https://doi.org/10.48550/arxiv.2302.06352"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2302.06352","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.06352","pdf_url":"https://arxiv.org/pdf/2302.06352","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2302.06352","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034573269","display_name":"Francesco Santini","orcid":"https://orcid.org/0000-0001-6984-4816"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Santini, Francesco","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081757049","display_name":"Jakob Wasserthal","orcid":"https://orcid.org/0000-0002-9921-5698"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wasserthal, Jakob","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066629135","display_name":"Abramo Agosti","orcid":"https://orcid.org/0000-0001-5706-3772"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Agosti, Abramo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033822190","display_name":"Xeni Deligianni","orcid":"https://orcid.org/0000-0001-9968-223X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deligianni, Xeni","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086101942","display_name":"Kevin R. Keene","orcid":"https://orcid.org/0000-0001-9300-9888"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Keene, Kevin R.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033804414","display_name":"Hermien E. Kan","orcid":"https://orcid.org/0000-0002-5772-7177"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kan, Hermien E.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103194945","display_name":"Stefan Sommer","orcid":"https://orcid.org/0000-0001-6784-0328"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sommer, Stefan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084788429","display_name":"Fengdan Wang","orcid":"https://orcid.org/0000-0002-1647-7634"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Fengdan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006699722","display_name":"Claudia Weidensteiner","orcid":"https://orcid.org/0009-0007-8272-3817"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weidensteiner, Claudia","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053070970","display_name":"Giulia Manco","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Manco, Giulia","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083732015","display_name":"Matteo Paoletti","orcid":"https://orcid.org/0000-0002-1221-7747"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Paoletti, Matteo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030741978","display_name":"Valentina Mazzoli","orcid":"https://orcid.org/0000-0002-6700-8424"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mazzoli, Valentina","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062564649","display_name":"Arjun Desai","orcid":"https://orcid.org/0000-0003-0645-3257"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Desai, Arjun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5001734076","display_name":"Anna Pichiecchio","orcid":"https://orcid.org/0000-0002-5654-4088"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pichiecchio, Anna","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":14,"corresponding_author_ids":["https://openalex.org/A5034573269"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":20,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9983999729156494,"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"}},"topics":[{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9983999729156494,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.9883999824523926,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9883999824523926,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7365067005157471},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.7227814197540283},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6514773964881897},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5956919193267822},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4885726869106293},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4596737027168274},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.432783842086792},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42156368494033813},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.12119874358177185},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08930182456970215}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7365067005157471},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.7227814197540283},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6514773964881897},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5956919193267822},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4885726869106293},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4596737027168274},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.432783842086792},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42156368494033813},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.12119874358177185},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08930182456970215},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2302.06352","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.06352","pdf_url":"https://arxiv.org/pdf/2302.06352","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2302.06352","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2302.06352","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-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2302.06352","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.06352","pdf_url":"https://arxiv.org/pdf/2302.06352","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5099999904632568}],"awards":[{"id":"https://openalex.org/G1154387297","display_name":"Self-Improving Collaborative Segmentation Platform for Magnetic Resonance Images","funder_award_id":"196515","funder_id":"https://openalex.org/F4320320924","funder_display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung"},{"id":"https://openalex.org/G65162470","display_name":null,"funder_award_id":"Swiss National Science Foundation (SNF)","funder_id":"https://openalex.org/F4320320924","funder_display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320320924","display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung","ror":"https://ror.org/00yjd3n13"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4321010562.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1981780420","https://openalex.org/W2182707996","https://openalex.org/W45233828","https://openalex.org/W2964988449","https://openalex.org/W2397952901","https://openalex.org/W2029380707","https://openalex.org/W4255934811","https://openalex.org/W2465382974","https://openalex.org/W2010229520","https://openalex.org/W4380075502"],"abstract_inverted_index":{"Purpose:":[0],"To":[1],"present":[2,173],"and":[3,30,62,68,81,115,196],"evaluate":[4],"Dafne":[5,32,95,128,184],"(deep":[6],"anatomical":[7],"federated":[8,26],"network),":[9],"a":[10,37,130],"freely":[11],"available":[12],"decentralized,":[13],"collaborative":[14],"deep":[15,51],"learning":[16,52,73,195],"system":[17],"for":[18,194],"the":[19,50,56,59,64,70,78,85,92,101,112,117,134,144,152,160,175],"semantic":[20,137],"segmentation":[21,138,188],"of":[22,111,119,136,143],"radiological":[23],"images":[24],"through":[25,116],"incremental":[27],"learning.":[28],"Materials":[29],"Methods:":[31],"is":[33,43,74,89],"free":[34],"software":[35],"with":[36],"client-server":[38],"architecture.":[39],"The":[40],"client":[41],"side":[42,80],"an":[44],"advanced":[45],"user":[46,65],"interface":[47],"that":[48],"applies":[49],"models":[53,161],"stored":[54],"on":[55,107,151,165],"server":[57],"to":[58,66,84],"user's":[60],"data":[61],"allows":[63],"check":[67],"refine":[69],"prediction.":[71],"Incremental":[72],"then":[75],"performed":[76],"at":[77],"client's":[79],"sent":[82],"back":[83],"server,":[86],"where":[87],"it":[88],"integrated":[90],"into":[91],"root":[93],"model.":[94],"was":[96],"evaluated":[97],"locally,":[98],"by":[99,148],"assessing":[100],"performance":[102,164],"gain":[103],"across":[104],"model":[105,181],"generations":[106],"38":[108],"MRI":[109],"datasets":[110],"lower":[113],"legs,":[114],"analysis":[118],"real-world":[120],"usage":[121],"statistics":[122],"(n":[123],"=":[124],"639":[125],"use-cases).":[126],"Results:":[127],"demonstrated":[129],"statistically":[131],"improvement":[132,186],"in":[133,174,187],"accuracy":[135],"over":[139,190],"time":[140],"(average":[141],"increase":[142],"Dice":[145],"Similarity":[146],"Coefficient":[147],"0.007":[149],"points/generation":[150],"local":[153],"validation":[154],"set,":[155],"p":[156],"&lt;":[157],"0.001).":[158],"Qualitatively,":[159],"showed":[162,185],"enhanced":[163],"various":[166],"radiologic":[167],"image":[168],"types,":[169],"including":[170],"those":[171],"not":[172],"initial":[176],"training":[177],"sets,":[178],"indicating":[179],"good":[180],"generalizability.":[182],"Conclusion:":[183],"quality":[189],"time,":[191],"demonstrating":[192],"potential":[193],"generalization.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
