{"id":"https://openalex.org/W4309165877","doi":"https://doi.org/10.1109/tmi.2022.3221898","title":"FRODO: An In-Depth Analysis of a System to Reject Outlier Samples From a Trained Neural Network","display_name":"FRODO: An In-Depth Analysis of a System to Reject Outlier Samples From a Trained Neural Network","publication_year":2022,"publication_date":"2022-11-14","ids":{"openalex":"https://openalex.org/W4309165877","doi":"https://doi.org/10.1109/tmi.2022.3221898","pmid":"https://pubmed.ncbi.nlm.nih.gov/36374875"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2022.3221898","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2022.3221898","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://repository.ubn.ru.nl/bitstream/handle/2066/292469/1/292469.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000906476","display_name":"Erdi \u00c7all\u0131","orcid":"https://orcid.org/0000-0003-3962-7276"},"institutions":[{"id":"https://openalex.org/I145872427","display_name":"Radboud University Nijmegen","ror":"https://ror.org/016xsfp80","country_code":"NL","type":"education","lineage":["https://openalex.org/I145872427"]},{"id":"https://openalex.org/I2802934949","display_name":"Radboud University Medical Center","ror":"https://ror.org/05wg1m734","country_code":"NL","type":"funder","lineage":["https://openalex.org/I2802934949"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Erdi Calli","raw_affiliation_strings":["Radboudumc, Nijmegen, GA, The Netherlands"],"raw_orcid":"https://orcid.org/0000-0003-3962-7276","affiliations":[{"raw_affiliation_string":"Radboudumc, Nijmegen, GA, The Netherlands","institution_ids":["https://openalex.org/I145872427","https://openalex.org/I2802934949"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042982766","display_name":"Bram van Ginneken","orcid":"https://orcid.org/0000-0003-2028-8972"},"institutions":[{"id":"https://openalex.org/I145872427","display_name":"Radboud University Nijmegen","ror":"https://ror.org/016xsfp80","country_code":"NL","type":"education","lineage":["https://openalex.org/I145872427"]},{"id":"https://openalex.org/I2802934949","display_name":"Radboud University Medical Center","ror":"https://ror.org/05wg1m734","country_code":"NL","type":"funder","lineage":["https://openalex.org/I2802934949"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Bram Van Ginneken","raw_affiliation_strings":["Radboudumc, Nijmegen, GA, The Netherlands"],"raw_orcid":"https://orcid.org/0000-0003-2028-8972","affiliations":[{"raw_affiliation_string":"Radboudumc, Nijmegen, GA, The Netherlands","institution_ids":["https://openalex.org/I145872427","https://openalex.org/I2802934949"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013479475","display_name":"Ecem Sogancioglu","orcid":"https://orcid.org/0000-0001-8850-8121"},"institutions":[{"id":"https://openalex.org/I145872427","display_name":"Radboud University Nijmegen","ror":"https://ror.org/016xsfp80","country_code":"NL","type":"education","lineage":["https://openalex.org/I145872427"]},{"id":"https://openalex.org/I2802934949","display_name":"Radboud University Medical Center","ror":"https://ror.org/05wg1m734","country_code":"NL","type":"funder","lineage":["https://openalex.org/I2802934949"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Ecem Sogancioglu","raw_affiliation_strings":["Radboudumc, Nijmegen, GA, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Radboudumc, Nijmegen, GA, The Netherlands","institution_ids":["https://openalex.org/I145872427","https://openalex.org/I2802934949"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053348129","display_name":"Keelin Murphy","orcid":"https://orcid.org/0000-0001-6831-4020"},"institutions":[{"id":"https://openalex.org/I145872427","display_name":"Radboud University Nijmegen","ror":"https://ror.org/016xsfp80","country_code":"NL","type":"education","lineage":["https://openalex.org/I145872427"]},{"id":"https://openalex.org/I2802934949","display_name":"Radboud University Medical Center","ror":"https://ror.org/05wg1m734","country_code":"NL","type":"funder","lineage":["https://openalex.org/I2802934949"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Keelin Murphy","raw_affiliation_strings":["Radboudumc, Nijmegen, GA, The Netherlands"],"raw_orcid":"https://orcid.org/0000-0001-6831-4020","affiliations":[{"raw_affiliation_string":"Radboudumc, Nijmegen, GA, The Netherlands","institution_ids":["https://openalex.org/I145872427","https://openalex.org/I2802934949"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5000906476"],"corresponding_institution_ids":["https://openalex.org/I145872427","https://openalex.org/I2802934949"],"apc_list":null,"apc_paid":null,"fwci":2.5988,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.8992708,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"42","issue":"4","first_page":"971","last_page":"981"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9995999932289124,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9995999932289124,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9984999895095825,"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":0.9760000109672546,"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/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.7798077464103699},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7343845367431641},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6693872213363647},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6429208517074585},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6030605435371399},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.5949413180351257},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5454509854316711},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49113985896110535},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3026235103607178}],"concepts":[{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.7798077464103699},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7343845367431641},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6693872213363647},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6429208517074585},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6030605435371399},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.5949413180351257},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5454509854316711},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49113985896110535},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3026235103607178}],"mesh":[{"descriptor_ui":"D012372","descriptor_name":"ROC Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012372","descriptor_name":"ROC Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012372","descriptor_name":"ROC Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1109/tmi.2022.3221898","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2022.3221898","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:36374875","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36374875","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on medical imaging","raw_type":null},{"id":"pmh:oai:repository.ubn.ru.nl:2066/292469","is_oa":true,"landing_page_url":"https://hdl.handle.net/2066/292469","pdf_url":"https://repository.ubn.ru.nl/bitstream/handle/2066/292469/1/292469.pdf","source":{"id":"https://openalex.org/S4306401067","display_name":"Radboud Repository (Radboud University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I145872427","host_organization_name":"Radboud University Nijmegen","host_organization_lineage":["https://openalex.org/I145872427"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article / Letter to editor"},{"id":"pmh:ru:oai:repository.ubn.ru.nl:2066/292469","is_oa":false,"landing_page_url":"http://hdl.handle.net/2066/292469","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Medical Imaging, 42, 971 - 981","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:repository.ubn.ru.nl:2066/292469","is_oa":true,"landing_page_url":"https://hdl.handle.net/2066/292469","pdf_url":"https://repository.ubn.ru.nl/bitstream/handle/2066/292469/1/292469.pdf","source":{"id":"https://openalex.org/S4306401067","display_name":"Radboud Repository (Radboud University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I145872427","host_organization_name":"Radboud University Nijmegen","host_organization_lineage":["https://openalex.org/I145872427"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article / Letter to editor"},"sustainable_development_goals":[{"score":0.5699999928474426,"display_name":"Life below water","id":"https://metadata.un.org/sdg/14"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4309165877.pdf","grobid_xml":"https://content.openalex.org/works/W4309165877.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1540596182","https://openalex.org/W1901129140","https://openalex.org/W2014918341","https://openalex.org/W2058568633","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2328176404","https://openalex.org/W2592929672","https://openalex.org/W2611650229","https://openalex.org/W2884585870","https://openalex.org/W2951597495","https://openalex.org/W3028577876","https://openalex.org/W3037355691","https://openalex.org/W3041905672","https://openalex.org/W3101156210","https://openalex.org/W3118608800","https://openalex.org/W3175716777","https://openalex.org/W3194400333","https://openalex.org/W3208979489","https://openalex.org/W6630210095","https://openalex.org/W6638667902","https://openalex.org/W6682778277","https://openalex.org/W6728622933","https://openalex.org/W6730042731","https://openalex.org/W6745891213","https://openalex.org/W6747899497","https://openalex.org/W6751494907","https://openalex.org/W6752760542","https://openalex.org/W6753123669","https://openalex.org/W6765696844","https://openalex.org/W6780405429","https://openalex.org/W6780542504","https://openalex.org/W6780874654","https://openalex.org/W6797713660"],"related_works":["https://openalex.org/W4382795578","https://openalex.org/W2355463328","https://openalex.org/W2402648945","https://openalex.org/W2053213469","https://openalex.org/W939486154","https://openalex.org/W1431147547","https://openalex.org/W2055761197","https://openalex.org/W2057608111","https://openalex.org/W4386482528","https://openalex.org/W3182289794"],"abstract_inverted_index":{"An":[0],"important":[1],"limitation":[2],"of":[3,46,77,100,121,143,164,167,190,199],"state-of-the-art":[4,211],"deep":[5],"learning":[6],"networks":[7],"is":[8,17,70,151,175,203],"that":[9,32,52,218],"they":[10,24],"do":[11],"not":[12],"recognize":[13],"when":[14],"their":[15,101],"input":[16,63,87],"dissimilar":[18],"to":[19,29,61,81,113,205,230],"the":[20,74,83,96,105,119,187,209,215],"data":[21,64],"on":[22,95,128],"which":[23],"were":[25],"trained":[26,59],"and":[27,116,135,169,193,225,233],"proceed":[28],"produce":[30],"outputs":[31,80,103],"will":[33],"be":[34,54,111,206,231],"unreliable":[35],"or":[36],"nonsensical.":[37],"In":[38],"this":[39],"work,":[40],"we":[41,117],"describe":[42],"FRODO":[43,72,122,183,219],"(Free":[44],"Rejection":[45],"Out-of-Distribution),":[47],"a":[48,66],"publicly":[49],"available":[50],"method":[51,109,212],"can":[53,110],"easily":[55],"employed":[56],"for":[57,132,153],"any":[58,114,223],"network":[60,224],"detect":[62],"from":[65,104],"different":[67,200],"distribution":[68,76],"than":[69],"expected.":[71],"uses":[73],"statistical":[75],"intermediate":[78],"layer":[79,102],"define":[82],"expected":[84],"in-distribution":[85,149],"(ID)":[86],"image":[88],"properties.":[89],"New":[90],"samples":[91,127,150,198],"are":[92,158],"judged":[93],"based":[94],"Mahalanobis":[97],"distance":[98],"(MD)":[99],"defined":[106,152],"distribution.":[107],"The":[108,155],"applied":[112],"network,":[115],"demonstrate":[118],"performance":[120,170],"in":[123,138,195],"correctly":[124],"rejecting":[125,172],"OOD":[126,162,197],"three":[129],"distinct":[130],"architectures":[131],"classification,":[133],"localization,":[134],"segmentation":[136],"tasks":[137],"chest":[139],"X-rays.":[140],"A":[141],"dataset":[142],"21,576":[144],"X-ray":[145],"images":[146,157],"with":[147,208,214,222],"3,655":[148],"testing.":[154],"remaining":[156],"divided":[159],"into":[160],"four":[161],"categories":[163],"varying":[165],"levels":[166],"difficulty,":[168],"at":[171],"each":[173],"type":[174],"evaluated":[176],"using":[177],"receiver":[178],"operating":[179],"characteristic":[180],"(ROC)":[181],"analysis.":[182],"achieves":[184],"areas":[185],"under":[186],"ROC":[188],"(AUC)":[189],"between":[191],"0.815":[192],"0.999":[194],"distinguishing":[196],"types.":[201],"This":[202],"shown":[204],"comparable":[207],"best-performing":[210],"tested,":[213],"substantial":[216],"advantage":[217],"integrates":[220],"seamlessly":[221],"requires":[226],"no":[227],"extra":[228],"model":[229],"constructed":[232],"trained.":[234]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
