{"id":"https://openalex.org/W7133337740","doi":"https://doi.org/10.48550/arxiv.2603.01098","title":"Differential privacy representation geometry for medical image analysis","display_name":"Differential privacy representation geometry for medical image analysis","publication_year":2026,"publication_date":"2026-03-01","ids":{"openalex":"https://openalex.org/W7133337740","doi":"https://doi.org/10.48550/arxiv.2603.01098"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.01098","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01098","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.01098","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076251937","display_name":"Soroosh Tayebi Arasteh","orcid":"https://orcid.org/0000-0003-1015-7733"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arasteh, Soroosh Tayebi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127985724","display_name":"Marziyeh Mohammadi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohammadi, Marziyeh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117184858","display_name":"Sven Nebelung","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nebelung, Sven","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Truhn, Daniel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Truhn, Daniel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":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":0.8738999962806702,"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":0.8738999962806702,"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":0.014000000432133675,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.010400000028312206,"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/differential-privacy","display_name":"Differential privacy","score":0.7164999842643738},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.711899995803833},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.5745000243186951},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5152999758720398},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4986000061035156},{"id":"https://openalex.org/keywords/differential","display_name":"Differential (mechanical device)","score":0.490200012922287},{"id":"https://openalex.org/keywords/displacement","display_name":"Displacement (psychology)","score":0.4814000129699707},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.46799999475479126},{"id":"https://openalex.org/keywords/differential-geometry","display_name":"Differential geometry","score":0.4580000042915344}],"concepts":[{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.7164999842643738},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.711899995803833},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.5745000243186951},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5152999758720398},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4986000061035156},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.490200012922287},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4887999892234802},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48660001158714294},{"id":"https://openalex.org/C107551265","wikidata":"https://www.wikidata.org/wiki/Q1458245","display_name":"Displacement (psychology)","level":2,"score":0.4814000129699707},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.46799999475479126},{"id":"https://openalex.org/C192939610","wikidata":"https://www.wikidata.org/wiki/Q188444","display_name":"Differential geometry","level":2,"score":0.4580000042915344},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4221000075340271},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4129999876022339},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.41269999742507935},{"id":"https://openalex.org/C112604564","wikidata":"https://www.wikidata.org/wiki/Q7489226","display_name":"Shape analysis (program analysis)","level":3,"score":0.40700000524520874},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.38199999928474426},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.3707999885082245},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.3662000000476837},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.35830000042915344},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3481000065803528},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3441999852657318},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.336899995803833},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33379998803138733},{"id":"https://openalex.org/C32990609","wikidata":"https://www.wikidata.org/wiki/Q306542","display_name":"Transformation geometry","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C192368570","wikidata":"https://www.wikidata.org/wiki/Q1789829","display_name":"Digital geometry","level":5,"score":0.3181999921798706},{"id":"https://openalex.org/C56435381","wikidata":"https://www.wikidata.org/wiki/Q1196371","display_name":"Geometric transformation","level":3,"score":0.3172000050544739},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3165999948978424},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.2962999939918518},{"id":"https://openalex.org/C154968394","wikidata":"https://www.wikidata.org/wiki/Q5535474","display_name":"Geometric analysis","level":5,"score":0.2702000141143799},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.267300009727478},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.2655999958515167},{"id":"https://openalex.org/C29123130","wikidata":"https://www.wikidata.org/wiki/Q874709","display_name":"Computational geometry","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.2596000134944916}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.01098","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01098","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.01098","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01098","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7462850213050842,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Differential":[0,24],"privacy":[1,178],"(DP)'s":[2],"effect":[3],"in":[4],"medical":[5],"imaging":[6],"is":[7,55,68,95,106,145],"typically":[8],"evaluated":[9],"only":[10],"through":[11],"end-to-end":[12,76,141],"performance,":[13],"leaving":[14],"the":[15,71,110,138],"mechanism":[16],"of":[17,41],"privacy-induced":[18,173],"utility":[19],"loss":[20],"unclear.":[21],"We":[22],"introduce":[23],"Privacy":[25],"Representation":[26],"Geometry":[27,54],"for":[28,171],"Medical":[29],"Imaging":[30],"(DP-RGMI),":[31],"a":[32,38,99,168],"framework":[33,170],"that":[34,93,124,137],"interprets":[35],"DP":[36,94,125],"as":[37,70,167],"structured":[39],"transformation":[40],"representation":[42,58,127],"space":[43],"and":[44,51,62,75,87,114,120,143,160,176],"decomposes":[45],"performance":[46,142],"degradation":[47],"into":[48],"encoder":[49],"geometry":[50],"task-head":[52],"utilization.":[53],"quantified":[56],"by":[57,152],"displacement":[59,113],"from":[60,82],"initialization":[61],"spectral":[63,115],"effective":[64],"dimension,":[65],"while":[66,154],"utilization":[67,100,144],"measured":[69],"gap":[72,101],"between":[73,140],"linear-probe":[74],"utility.":[77],"Across":[78],"over":[79],"594,000":[80],"images":[81],"four":[83],"chest":[84],"X-ray":[85],"datasets":[86,148],"multiple":[88],"pretrained":[89],"initializations,":[90],"we":[91],"show":[92],"consistently":[96],"associated":[97],"with":[98],"even":[102],"when":[103],"linear":[104],"separability":[105],"largely":[107],"preserved.":[108],"At":[109],"same":[111],"time,":[112],"dimension":[116],"exhibit":[117],"non-monotonic,":[118],"initialization-":[119],"dataset-dependent":[121],"reshaping,":[122],"indicating":[123],"alters":[126],"anisotropy":[128],"rather":[129],"than":[130],"uniformly":[131],"collapsing":[132],"features.":[133],"Correlation":[134],"analysis":[135],"reveals":[136],"association":[139],"robust":[146],"across":[147],"but":[149],"can":[150],"vary":[151],"initialization,":[153],"geometric":[155],"quantities":[156],"capture":[157],"additional":[158],"prior-":[159],"dataset-conditioned":[161],"variation.":[162],"These":[163],"findings":[164],"position":[165],"DP-RGMI":[166],"reproducible":[169],"diagnosing":[172],"failure":[174],"modes":[175],"informing":[177],"model":[179],"selection.":[180]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-04T00:00:00"}