{"id":"https://openalex.org/W4221034530","doi":"https://doi.org/10.1117/12.2608120","title":"Unsupervised anomaly detection in 3D brain MRI using deep learning with multi-task brain age prediction","display_name":"Unsupervised anomaly detection in 3D brain MRI using deep learning with multi-task brain age prediction","publication_year":2022,"publication_date":"2022-04-01","ids":{"openalex":"https://openalex.org/W4221034530","doi":"https://doi.org/10.1117/12.2608120"},"language":"en","primary_location":{"id":"doi:10.1117/12.2608120","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2608120","pdf_url":null,"source":{"id":"https://openalex.org/S4363606689","display_name":"Medical Imaging 2022: Computer-Aided Diagnosis","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2022: Computer-Aided Diagnosis","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/A5070915368","display_name":"Marcel Bengs","orcid":"https://orcid.org/0000-0002-2229-9547"},"institutions":[{"id":"https://openalex.org/I884043246","display_name":"Hamburg University of Technology","ror":"https://ror.org/04bs1pb34","country_code":"DE","type":"education","lineage":["https://openalex.org/I884043246"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Marcel Bengs","raw_affiliation_strings":["Technische Univ. Hamburg-Harburg (Germany)"],"affiliations":[{"raw_affiliation_string":"Technische Univ. Hamburg-Harburg (Germany)","institution_ids":["https://openalex.org/I884043246"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083173883","display_name":"Finn Behrendt","orcid":"https://orcid.org/0000-0001-7191-6508"},"institutions":[{"id":"https://openalex.org/I884043246","display_name":"Hamburg University of Technology","ror":"https://ror.org/04bs1pb34","country_code":"DE","type":"education","lineage":["https://openalex.org/I884043246"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Finn Behrendt","raw_affiliation_strings":["Technische Univ. Hamburg-Harburg (Germany)"],"affiliations":[{"raw_affiliation_string":"Technische Univ. Hamburg-Harburg (Germany)","institution_ids":["https://openalex.org/I884043246"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071989904","display_name":"Max-Heinrich Laves","orcid":"https://orcid.org/0000-0003-0156-7247"},"institutions":[{"id":"https://openalex.org/I884043246","display_name":"Hamburg University of Technology","ror":"https://ror.org/04bs1pb34","country_code":"DE","type":"education","lineage":["https://openalex.org/I884043246"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Max-Heinrich Laves","raw_affiliation_strings":["Technische Univ. Hamburg-Harburg (Germany)"],"affiliations":[{"raw_affiliation_string":"Technische Univ. Hamburg-Harburg (Germany)","institution_ids":["https://openalex.org/I884043246"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031373312","display_name":"Julia Kr\u00fcger","orcid":"https://orcid.org/0000-0001-9963-4588"},"institutions":[{"id":"https://openalex.org/I124348172","display_name":"Jungheinrich (Germany)","ror":"https://ror.org/03znz6n75","country_code":"DE","type":"company","lineage":["https://openalex.org/I124348172"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Julia Kr\u00fcger","raw_affiliation_strings":["jung diagnostics GmbH (Germany)"],"affiliations":[{"raw_affiliation_string":"jung diagnostics GmbH (Germany)","institution_ids":["https://openalex.org/I124348172"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057079579","display_name":"Roland Opfer","orcid":"https://orcid.org/0000-0002-9911-5478"},"institutions":[{"id":"https://openalex.org/I124348172","display_name":"Jungheinrich (Germany)","ror":"https://ror.org/03znz6n75","country_code":"DE","type":"company","lineage":["https://openalex.org/I124348172"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Roland Opfer","raw_affiliation_strings":["jung diagnostics GmbH (Germany)"],"affiliations":[{"raw_affiliation_string":"jung diagnostics GmbH (Germany)","institution_ids":["https://openalex.org/I124348172"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087348362","display_name":"Alexander Schlaefer","orcid":"https://orcid.org/0000-0001-9201-8854"},"institutions":[{"id":"https://openalex.org/I884043246","display_name":"Hamburg University of Technology","ror":"https://ror.org/04bs1pb34","country_code":"DE","type":"education","lineage":["https://openalex.org/I884043246"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Alexander Schlaefer","raw_affiliation_strings":["Technische Univ. Hamburg-Harburg (Germany)"],"affiliations":[{"raw_affiliation_string":"Technische Univ. Hamburg-Harburg (Germany)","institution_ids":["https://openalex.org/I884043246"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5070915368"],"corresponding_institution_ids":["https://openalex.org/I884043246"],"apc_list":null,"apc_paid":null,"fwci":0.9393,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.75571103,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"35","last_page":"35"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9995999932289124,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9995999932289124,"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":0.9986000061035156,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9980000257492065,"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/computer-science","display_name":"Computer science","score":0.6883382797241211},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6848433017730713},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6550651788711548},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.649044394493103},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.5394881367683411},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.491534560918808},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4902506470680237},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.44866687059402466},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4153846502304077},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37738850712776184},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.13980922102928162},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.10752755403518677}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6883382797241211},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6848433017730713},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6550651788711548},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.649044394493103},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.5394881367683411},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.491534560918808},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4902506470680237},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.44866687059402466},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4153846502304077},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37738850712776184},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.13980922102928162},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.10752755403518677},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1117/12.2608120","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2608120","pdf_url":null,"source":{"id":"https://openalex.org/S4363606689","display_name":"Medical Imaging 2022: Computer-Aided Diagnosis","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2022: Computer-Aided Diagnosis","raw_type":"proceedings-article"},{"id":"pmh:oai:tore.tuhh.de:11420/13059","is_oa":false,"landing_page_url":"http://hdl.handle.net/11420/13059","pdf_url":null,"source":{"id":"https://openalex.org/S4306401751","display_name":"tub.dok (Hamburg University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I884043246","host_organization_name":"Hamburg University of Technology","host_organization_lineage":["https://openalex.org/I884043246"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5899999737739563,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1641498739","https://openalex.org/W1959608418","https://openalex.org/W2168199261","https://openalex.org/W2751069891","https://openalex.org/W2900298334","https://openalex.org/W2900954917","https://openalex.org/W2904300281","https://openalex.org/W2961560364","https://openalex.org/W2990366895","https://openalex.org/W3118868805","https://openalex.org/W3157328277","https://openalex.org/W3178092667","https://openalex.org/W3184778778","https://openalex.org/W3191370428","https://openalex.org/W4241226853","https://openalex.org/W4251082071","https://openalex.org/W6640963894","https://openalex.org/W6750599543","https://openalex.org/W6755891590","https://openalex.org/W6756793739","https://openalex.org/W6762617148","https://openalex.org/W6765220112","https://openalex.org/W6768926752","https://openalex.org/W6780802069","https://openalex.org/W6787615950","https://openalex.org/W6799766821"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969","https://openalex.org/W3120251014"],"abstract_inverted_index":{"Lesion":[0],"detection":[1,31],"in":[2,33,86,96],"brain":[3,34,61,70,77,98],"Magnetic":[4],"Resonance":[5],"Images":[6],"(MRIs)":[7],"remains":[8],"a":[9,23,45,130],"challenging":[10],"task.":[11],"MRIs":[12,145],"are":[13],"typically":[14],"read":[15],"and":[16,25,79,118,150],"interpreted":[17],"by":[18],"domain":[19],"experts,":[20],"which":[21,83],"is":[22,72,84],"tedious":[24],"time-consuming":[26],"process.":[27],"Recently,":[28],"unsupervised":[29],"anomaly":[30,64,116],"(UAD)":[32],"MRI":[35,99],"with":[36,88,137,168],"deep":[37,92,132],"learning":[38,93,133],"has":[39],"shown":[40],"promising":[41],"results":[42],"to":[43,174],"provide":[44],"quick,":[46],"initial":[47],"assessment.":[48],"So":[49],"far,":[50],"these":[51],"methods":[52],"only":[53],"rely":[54],"on":[55,125],"the":[56,73,76,80,106,151],"visual":[57],"appearance":[58],"of":[59,108,146,171,177],"healthy":[60,148],"anatomy":[62],"for":[63,68,94,135,158],"detection.":[65],"Another":[66],"biomarker":[67],"abnormal":[69],"development":[71],"deviation":[74],"between":[75],"age":[78,102,109,139,183],"chronological":[81],"age,":[82],"unexplored":[85],"combination":[87],"UAD.":[89],"We":[90,104,141],"propose":[91,129],"UAD":[95,136,166],"3D":[97],"considering":[100],"additional":[101,115],"information.":[103,184],"analyze":[105],"value":[107],"information":[110],"during":[111],"training,":[112],"as":[113],"an":[114,169,175],"score,":[117],"systematically":[119],"study":[120],"several":[121],"architecture":[122],"concepts.":[123],"Based":[124],"our":[126,159],"analysis,":[127],"we":[128],"novel":[131,162],"approach":[134,163],"multi-task":[138],"prediction.":[140],"use":[142],"clinical":[143],"T1-weighted":[144],"1735":[147],"subjects":[149],"publicly":[152],"available":[153],"BraTs":[154],"2019":[155],"data":[156],"set":[157],"study.":[160],"Our":[161],"significantly":[164],"improves":[165],"performance":[167],"AUC":[170],"92.60%":[172],"compared":[173],"AUC-score":[176],"84.37%":[178],"using":[179],"previous":[180],"approaches":[181],"without":[182]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}