{"id":"https://openalex.org/W4386362588","doi":"https://doi.org/10.1109/isbi53787.2023.10230809","title":"Federated Semi-Supervised Segmentation with Randomized Weight Perturbation","display_name":"Federated Semi-Supervised Segmentation with Randomized Weight Perturbation","publication_year":2023,"publication_date":"2023-04-18","ids":{"openalex":"https://openalex.org/W4386362588","doi":"https://doi.org/10.1109/isbi53787.2023.10230809"},"language":"en","primary_location":{"id":"doi:10.1109/isbi53787.2023.10230809","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/isbi53787.2023.10230809","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"article","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/A5048054713","display_name":"Minhyeong Yu","orcid":"https://orcid.org/0000-0002-0350-4349"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minhyeong Yu","raw_affiliation_strings":["Korea University,Department of Computer Science and Engineering,Seoul,Republic of Korea","Department of Computer Science and Engineering, Korea University, Seoul, Republic of Korea","DeepingSource Inc, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea University,Department of Computer Science and Engineering,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Korea University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"DeepingSource Inc, Seoul, Republic of Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100733416","display_name":"Sunwoo Kim","orcid":"https://orcid.org/0000-0002-6449-7576"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sunwoo Kim","raw_affiliation_strings":["Korea University,Department of Computer Science and Engineering,Seoul,Republic of Korea","Department of Computer Science and Engineering, Korea University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea University,Department of Computer Science and Engineering,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Korea University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110957263","display_name":"Seungjun Baek","orcid":null},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seungjun Baek","raw_affiliation_strings":["Korea University,Department of Computer Science and Engineering,Seoul,Republic of Korea","Department of Computer Science and Engineering, Korea University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea University,Department of Computer Science and Engineering,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Korea University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10501942,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9980999827384949,"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":0.9980999827384949,"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":0.9980999827384949,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9836999773979187,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7711405754089355},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6790130734443665},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5493122339248657},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5228527188301086},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.41879117488861084},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.41638848185539246},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32963088154792786}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7711405754089355},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6790130734443665},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5493122339248657},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5228527188301086},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.41879117488861084},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.41638848185539246},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32963088154792786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi53787.2023.10230809","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/isbi53787.2023.10230809","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2095705004","https://openalex.org/W2953070460","https://openalex.org/W2962369866","https://openalex.org/W2963183964","https://openalex.org/W3001197829","https://openalex.org/W3107695429","https://openalex.org/W3118629228","https://openalex.org/W3127057363","https://openalex.org/W3147359051","https://openalex.org/W3150684546","https://openalex.org/W3171581326","https://openalex.org/W3207000431","https://openalex.org/W4224989742","https://openalex.org/W4318619660","https://openalex.org/W6639824700","https://openalex.org/W6674330103","https://openalex.org/W6728757088","https://openalex.org/W6733814495","https://openalex.org/W6765939562","https://openalex.org/W6773005947","https://openalex.org/W6784265214","https://openalex.org/W6788603650"],"related_works":["https://openalex.org/W1603736412","https://openalex.org/W4304185162","https://openalex.org/W4379231730","https://openalex.org/W2061685118","https://openalex.org/W3006282800","https://openalex.org/W2462100143","https://openalex.org/W1770503332","https://openalex.org/W3125207769","https://openalex.org/W4389858081","https://openalex.org/W2577825108"],"abstract_inverted_index":{"Medical":[0],"image":[1],"segmentation":[2,162],"is":[3,151],"challenging":[4],"because":[5],"of":[6,8,14],"lack":[7],"annotated":[9],"data":[10],"and":[11,25,62,118,140,150,164],"the":[12,54,89,128,136,145],"reluctance":[13],"institutions":[15],"sharing":[16],"sensitive":[17],"patient":[18],"information.":[19],"Recent":[20],"advances":[21],"in":[22,34,52,72,83],"federated":[23,44],"learning":[24,27],"semi-supervised":[26,45,69,122],"enable":[28],"training":[29],"models":[30,65,80,93],"with":[31,59],"limited":[32],"labels":[33],"a":[35,41,84,110,159],"privacy-preserving":[36],"manner.":[37],"We":[38,131],"propose":[39,101],"FedWeP,":[40],"method":[42,107],"for":[43,68,98],"segmentation.":[46],"FedWeP":[47,143],"uses":[48],"Randomized":[49],"Weight":[50],"Perturbation":[51],"which":[53,99],"server":[55,117],"modulates":[56],"model":[57,112],"weights":[58],"Gaussian":[60],"noise,":[61],"disseminates":[63],"perturbed":[64,82,92],"to":[66,74,113,153],"clients":[67],"training.":[70],"Moreover,":[71],"order":[73],"facilitate":[75],"consistency":[76],"regularization":[77],"at":[78],"clients,":[79,119],"are":[81],"controlled":[85],"way":[86],"so":[87],"that":[88,142],"predictions":[90],"from":[91],"do":[94],"not":[95],"deviate":[96],"excessively,":[97],"we":[100],"similarity-based":[102],"seed":[103],"search.":[104],"Importantly,":[105],"our":[106,133],"requires":[108],"only":[109],"single":[111],"be":[114],"exchanged":[115],"between":[116,161],"unlike":[120],"conventional":[121],"methods":[123],"using":[124,135,147,155],"two":[125,156],"models,":[126,157],"halving":[127],"communication":[129,165],"costs.":[130,166],"validate":[132],"approach":[134],"COVID-19":[137],"infection":[138],"dataset,":[139],"demonstrate":[141],"outperforms":[144],"baseline":[146],"one":[148],"model,":[149],"comparable":[152],"those":[154],"striking":[158],"balance":[160],"performance":[163]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}