{"id":"https://openalex.org/W7134848664","doi":"https://doi.org/10.48550/arxiv.2603.07142","title":"PDD: Manifold-Prior Diverse Distillation for Medical Anomaly Detection","display_name":"PDD: Manifold-Prior Diverse Distillation for Medical Anomaly Detection","publication_year":2026,"publication_date":"2026-03-07","ids":{"openalex":"https://openalex.org/W7134848664","doi":"https://doi.org/10.48550/arxiv.2603.07142"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.07142","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102665696","display_name":"Xijun Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Xijun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128683207","display_name":"Hongying Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Hongying","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128688810","display_name":"Fanhua Shang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shang, Fanhua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066925216","display_name":"Yanming Hui","orcid":"https://orcid.org/0000-0001-8982-8709"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hui, Yanming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128635519","display_name":"Liang Wan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wan, Liang","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26835553,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9200000166893005,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9200000166893005,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.011099999770522118,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.008200000040233135,"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/anomaly-detection","display_name":"Anomaly detection","score":0.6798999905586243},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.58160001039505},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5601999759674072},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5565999746322632},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.5383999943733215},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5224999785423279},{"id":"https://openalex.org/keywords/manifold-alignment","display_name":"Manifold alignment","score":0.482699990272522},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4763000011444092},{"id":"https://openalex.org/keywords/unification","display_name":"Unification","score":0.45829999446868896}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6798999905586243},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6118000149726868},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.58160001039505},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5601999759674072},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5565999746322632},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5472999811172485},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.5383999943733215},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5224999785423279},{"id":"https://openalex.org/C153120616","wikidata":"https://www.wikidata.org/wiki/Q17068315","display_name":"Manifold alignment","level":4,"score":0.482699990272522},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4763000011444092},{"id":"https://openalex.org/C96146094","wikidata":"https://www.wikidata.org/wiki/Q609057","display_name":"Unification","level":2,"score":0.45829999446868896},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.43470001220703125},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41600000858306885},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4106999933719635},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.4043999910354614},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4023999869823456},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.39649999141693115},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3871999979019165},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.3700000047683716},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34389999508857727},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29319998621940613},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.2906000018119812},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.25600001215934753},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.2540000081062317}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.07142","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.07142","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.07142","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"pmh:doi:10.48550/arxiv.2603.07142","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"score":0.7552909255027771,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Medical":[0],"image":[1,197],"anomaly":[2,198],"detection":[3,148],"faces":[4],"unique":[5],"challenges":[6],"due":[7],"to":[8,136,168],"subtle,":[9],"heterogeneous":[10],"anomalies":[11],"embedded":[12],"in":[13,173,184,195],"complex":[14],"anatomical":[15],"structures.":[16],"Through":[17],"systematic":[18],"Grad-CAM":[19],"analysis,":[20],"we":[21],"reveal":[22],"that":[23,51,157],"discriminative":[24],"activation":[25],"maps":[26],"fail":[27],"on":[28,34,152,175,187],"medical":[29,154,196],"data,":[30],"unlike":[31],"their":[32],"success":[33],"industrial":[35],"datasets,":[36,180],"motivating":[37],"the":[38,124,188],"need":[39],"for":[40,120],"manifold-level":[41],"modeling.":[42],"We":[43],"propose":[44],"PDD":[45,158],"(Manifold-Prior":[46],"Diverse":[47],"Distillation),":[48],"a":[49,56,89,130],"framework":[50],"unifies":[52],"dual-teacher":[53],"priors":[54],"into":[55,64,111],"shared":[57],"high-dimensional":[58],"manifold":[59,108],"and":[60,73,79,92,171,178,182],"distills":[61],"this":[62],"knowledge":[63],"dual":[65],"students":[66],"with":[67],"complementary":[68],"behaviors.":[69],"Specifically,":[70],"frozen":[71],"VMamba-Tiny":[72],"wide-ResNet50":[74],"encoders":[75],"provide":[76],"global":[77],"contextual":[78],"local":[80,121],"structural":[81],"priors,":[82],"respectively.":[83],"Their":[84],"features":[85],"are":[86],"unified":[87,107],"through":[88,129],"Manifold":[90,131],"Matching":[91],"Unification":[93],"(MMU)":[94],"module,":[95],"while":[96,123,146],"an":[97],"Inter-Level":[98],"Feature":[99],"Adaption":[100],"(InA)":[101],"module":[102,135],"enriches":[103],"intermediate":[104],"representations.":[105],"The":[106,200],"is":[109],"distilled":[110],"two":[112],"students:":[113],"one":[114],"performs":[115],"layer-wise":[116],"distillation":[117],"via":[118],"InA":[119],"consistency,":[122],"other":[125],"receives":[126],"skip-projected":[127],"representations":[128],"Prior":[132],"Affine":[133],"(MPA)":[134],"capture":[137],"cross-layer":[138],"dependencies.":[139],"A":[140],"diversity":[141],"loss":[142],"prevents":[143],"representation":[144],"collapse":[145],"maintaining":[147],"sensitivity.":[149],"Extensive":[150],"experiments":[151],"multiple":[153],"datasets":[155],"demonstrate":[156],"significantly":[159],"outperforms":[160],"existing":[161],"state-of-the-art":[162,193],"methods,":[163],"achieving":[164],"improvements":[165],"of":[166],"up":[167],"11.8%,":[169],"5.1%,":[170],"8.5%":[172],"AUROC":[174],"HeadCT,":[176],"BrainMRI,":[177],"ZhangLab":[179],"respectively,":[181],"3.4%":[183],"F1":[185],"max":[186],"Uni-Medical":[189],"dataset,":[190],"establishing":[191],"new":[192],"performance":[194],"detection.":[199],"implementation":[201],"will":[202],"be":[203],"released":[204],"at":[205],"https://github.com/OxygenLu/PDD":[206]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-11T00:00:00"}
