{"id":"https://openalex.org/W4399118916","doi":"https://doi.org/10.1109/tim.2024.3406792","title":"Anomaly Detection for Medical Images Using Teacher\u2013Student Model With Skip Connections and Multiscale Anomaly Consistency","display_name":"Anomaly Detection for Medical Images Using Teacher\u2013Student Model With Skip Connections and Multiscale Anomaly Consistency","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4399118916","doi":"https://doi.org/10.1109/tim.2024.3406792"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2024.3406792","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tim.2024.3406792","pdf_url":"https://ieeexplore.ieee.org/ielx7/19/4407674/10540605.pdf","source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://ieeexplore.ieee.org/ielx7/19/4407674/10540605.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101513317","display_name":"Mingxuan Liu","orcid":"https://orcid.org/0009-0005-9456-015X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mingxuan Liu","raw_affiliation_strings":["School of Biomedical Engineering, Tsinghua University, Beijing, China","Department of Biomedical Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Biomedical Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006681354","display_name":"Yunrui Jiao","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunrui Jiao","raw_affiliation_strings":["School of Integrated Circuits, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Integrated Circuits, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067350353","display_name":"Jingqiao L\u00fc","orcid":"https://orcid.org/0009-0009-8878-0235"},"institutions":[{"id":"https://openalex.org/I117532281","display_name":"Guangzhou University of Chinese Medicine","ror":"https://ror.org/03qb7bg95","country_code":"CN","type":"education","lineage":["https://openalex.org/I117532281"]},{"id":"https://openalex.org/I4210135175","display_name":"Hefei Institute of Technology Innovation","ror":"https://ror.org/044wmmj34","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210135175"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingqiao Lu","raw_affiliation_strings":["XIN-Huangpu Joint Innovation Institute of Chinese Medicine, Guangzhou, China","Health Testing Technique and Equipment Research Center, Huangpu Joint Innovation Institute of Chinese Medicine, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"XIN-Huangpu Joint Innovation Institute of Chinese Medicine, Guangzhou, China","institution_ids":["https://openalex.org/I117532281"]},{"raw_affiliation_string":"Health Testing Technique and Equipment Research Center, Huangpu Joint Innovation Institute of Chinese Medicine, Guangzhou, China","institution_ids":["https://openalex.org/I4210135175"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100420459","display_name":"Hong Chen","orcid":"https://orcid.org/0000-0003-0774-1410"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Chen","raw_affiliation_strings":["School of Integrated Circuits, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Integrated Circuits, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101513317"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":3.1276,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.92395809,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"73","issue":null,"first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9783999919891357,"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":0.9783999919891357,"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/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.9258999824523926,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.815683126449585},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.8108835816383362},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.7023444771766663},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6605364084243774},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4944162368774414},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39456313848495483},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31098777055740356},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.16058623790740967},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.14347141981124878},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1287398636341095}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.815683126449585},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.8108835816383362},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.7023444771766663},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6605364084243774},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4944162368774414},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39456313848495483},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31098777055740356},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.16058623790740967},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.14347141981124878},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1287398636341095},{"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":1,"locations":[{"id":"doi:10.1109/tim.2024.3406792","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tim.2024.3406792","pdf_url":"https://ieeexplore.ieee.org/ielx7/19/4407674/10540605.pdf","source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/tim.2024.3406792","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tim.2024.3406792","pdf_url":"https://ieeexplore.ieee.org/ielx7/19/4407674/10540605.pdf","source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3919743371","display_name":null,"funder_award_id":"92164110","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G691677441","display_name":null,"funder_award_id":"62334014","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4399118916.pdf"},"referenced_works_count":85,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2158698691","https://openalex.org/W2293078015","https://openalex.org/W2599354622","https://openalex.org/W2618530766","https://openalex.org/W2788633781","https://openalex.org/W2914570111","https://openalex.org/W2948982773","https://openalex.org/W2963045681","https://openalex.org/W2964137095","https://openalex.org/W2978971541","https://openalex.org/W2991372685","https://openalex.org/W3001941893","https://openalex.org/W3023868590","https://openalex.org/W3026430594","https://openalex.org/W3033099853","https://openalex.org/W3034314048","https://openalex.org/W3092704883","https://openalex.org/W3096831136","https://openalex.org/W3112221804","https://openalex.org/W3118600296","https://openalex.org/W3139487216","https://openalex.org/W3147184966","https://openalex.org/W3166117684","https://openalex.org/W3166166117","https://openalex.org/W3169077988","https://openalex.org/W3169651898","https://openalex.org/W3171079288","https://openalex.org/W3175238080","https://openalex.org/W3175716777","https://openalex.org/W3180076059","https://openalex.org/W3189556521","https://openalex.org/W3193992273","https://openalex.org/W3195516695","https://openalex.org/W3198409653","https://openalex.org/W3200904534","https://openalex.org/W3203598078","https://openalex.org/W3205363811","https://openalex.org/W3207017437","https://openalex.org/W3208797540","https://openalex.org/W3211391700","https://openalex.org/W3215273707","https://openalex.org/W4206020427","https://openalex.org/W4206081240","https://openalex.org/W4224999518","https://openalex.org/W4225298409","https://openalex.org/W4287683516","https://openalex.org/W4287887190","https://openalex.org/W4288096081","https://openalex.org/W4289537725","https://openalex.org/W4289656451","https://openalex.org/W4290964450","https://openalex.org/W4295308550","https://openalex.org/W4311415873","https://openalex.org/W4312289809","https://openalex.org/W4312364701","https://openalex.org/W4312691731","https://openalex.org/W4312721464","https://openalex.org/W4312772600","https://openalex.org/W4313229732","https://openalex.org/W4317418443","https://openalex.org/W4324044570","https://openalex.org/W4362500858","https://openalex.org/W4375928989","https://openalex.org/W4376607822","https://openalex.org/W4377130839","https://openalex.org/W4377695098","https://openalex.org/W4377971351","https://openalex.org/W4379116586","https://openalex.org/W4380988244","https://openalex.org/W4385187407","https://openalex.org/W4386598243","https://openalex.org/W4386813353","https://openalex.org/W4387123819","https://openalex.org/W4390024648","https://openalex.org/W4390481153","https://openalex.org/W6631190155","https://openalex.org/W6777869702","https://openalex.org/W6778207253","https://openalex.org/W6780405429","https://openalex.org/W6781988083","https://openalex.org/W6797053244","https://openalex.org/W6799854401","https://openalex.org/W6802573413","https://openalex.org/W6853095873"],"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/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4377864969","https://openalex.org/W2972971679"],"abstract_inverted_index":{"Anomaly":[0],"detection":[1,174],"(AD)":[2],"in":[3,16,55,78,203],"medical":[4,79,184,189],"images":[5,128,157],"aims":[6],"to":[7,13,34,82,87,122,144,148,170],"recognize":[8],"test-time":[9],"abnormal":[10],"inputs":[11],"according":[12],"normal":[14,154],"samples":[15],"the":[17,24,43,84,99,108,119,124,130,133,145,150,172,196],"training":[18],"set.":[19],"Knowledge":[20],"distillation":[21,74],"based":[22],"on":[23,181,207],"teacher-student":[25],"(T-S)":[26],"model":[27,62,147],"is":[28,40,68,103,112,136],"a":[29,60,104,113,164],"simple":[30],"and":[31,47,107,175,186,201,209,214],"effective":[32],"method":[33],"identify":[35],"anomalies,":[36],"yet":[37],"its":[38],"efficacy":[39],"constrained":[41],"by":[42,70,90,199],"similarity":[44],"between":[45],"teacher":[46,100],"student":[48,109],"network":[49,101,110],"architectures.":[50],"To":[51],"address":[52],"this":[53,56],"problem,":[54],"paper,":[57],"we":[58,93,140,162],"propose":[59],"T-S":[61,146],"with":[63],"skip":[64,142],"connections":[65,143],"(Skip-TS)":[66],"which":[67,135],"trained":[69],"direct":[71],"reverse":[72],"knowledge":[73],"(DRKD)":[75],"for":[76],"AD":[77],"images.":[80],"First,":[81],"overcome":[83],"low":[85],"sensitivity":[86],"anomalies":[88],"caused":[89],"structural":[91],"similarity,":[92],"design":[94,163],"an":[95],"encoder-decoder":[96],"architecture":[97],"where":[98],"(T-Net)":[102],"pre-trained":[105],"encoder":[106],"(S-Net)":[111],"randomly":[114],"initialized":[115],"decoder.":[116],"During":[117],"training,":[118],"S-Net":[120,151],"learns":[121],"reconstruct":[123],"shallow":[125],"representations":[126],"of":[127,132,156,205],"from":[129,152],"output":[131],"T-Net,":[134],"called":[137],"DRKD.":[138],"Secondly,":[139],"introduce":[141],"prevent":[149],"missing":[153],"information":[155],"at":[158,221],"multi-scale.":[159],"In":[160],"addition,":[161],"multi-scale":[165],"anomaly":[166,173],"consistency":[167],"(MAC)":[168],"loss":[169],"improve":[171],"localization":[176],"performance.":[177],"Thorough":[178],"experiments":[179],"conducted":[180],"twelve":[182],"public":[183,208],"datasets":[185,190,217],"two":[187],"private":[188,210],"demonstrate":[191],"that":[192],"our":[193],"approach":[194],"surpasses":[195],"current":[197],"state-of-the-art":[198],"6.4%":[200],"8.2%":[202],"terms":[204],"AUROC":[206],"datasets,":[211],"respectively.":[212],"Code":[213],"organized":[215],"benchmark":[216],"will":[218],"be":[219],"available":[220],"https://github.com/Arktis2022/Skip-TS.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}