{"id":"https://openalex.org/W4391331245","doi":"https://doi.org/10.1109/smc53992.2023.10393874","title":"Refining Multi-Teacher Distillation for Multi-Modality COVID-19 Medical Images: Make the Best Decision","display_name":"Refining Multi-Teacher Distillation for Multi-Modality COVID-19 Medical Images: Make the Best Decision","publication_year":2023,"publication_date":"2023-10-01","ids":{"openalex":"https://openalex.org/W4391331245","doi":"https://doi.org/10.1109/smc53992.2023.10393874"},"language":"en","primary_location":{"id":"doi:10.1109/smc53992.2023.10393874","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/smc53992.2023.10393874","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5114461956","display_name":"Xiaoyu Pan","orcid":"https://orcid.org/0009-0004-3409-7987"},"institutions":[{"id":"https://openalex.org/I87780372","display_name":"Chongqing Medical University","ror":"https://ror.org/017z00e58","country_code":"CN","type":"education","lineage":["https://openalex.org/I87780372"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Pan","raw_affiliation_strings":["College of Medical Informatics, ChongQing Medical University,ChongQing,China","College of Medical Informatics, ChongQing Medical University, ChongQing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Medical Informatics, ChongQing Medical University,ChongQing,China","institution_ids":["https://openalex.org/I87780372"]},{"raw_affiliation_string":"College of Medical Informatics, ChongQing Medical University, ChongQing, China","institution_ids":["https://openalex.org/I87780372"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100669028","display_name":"Yuanyuan Jia","orcid":"https://orcid.org/0000-0002-5155-2185"},"institutions":[{"id":"https://openalex.org/I87780372","display_name":"Chongqing Medical University","ror":"https://ror.org/017z00e58","country_code":"CN","type":"education","lineage":["https://openalex.org/I87780372"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanyuan Jia","raw_affiliation_strings":["College of Medical Informatics, ChongQing Medical University,ChongQing,China","College of Medical Informatics, ChongQing Medical University, ChongQing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Medical Informatics, ChongQing Medical University,ChongQing,China","institution_ids":["https://openalex.org/I87780372"]},{"raw_affiliation_string":"College of Medical Informatics, ChongQing Medical University, ChongQing, China","institution_ids":["https://openalex.org/I87780372"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I87780372"],"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":"4202","last_page":"4207"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9998000264167786,"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":0.9998000264167786,"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/T10862","display_name":"AI in cancer detection","score":0.9750999808311462,"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":0.9537000060081482,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/refining","display_name":"Refining (metallurgy)","score":0.8375518321990967},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.7852247953414917},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.650589108467102},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6263397932052612},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.5623753070831299},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4511895477771759},{"id":"https://openalex.org/keywords/process-engineering","display_name":"Process engineering","score":0.3708595633506775},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16626888513565063},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.14560359716415405},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.13508164882659912},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.11458718776702881}],"concepts":[{"id":"https://openalex.org/C60044698","wikidata":"https://www.wikidata.org/wiki/Q1283324","display_name":"Refining (metallurgy)","level":2,"score":0.8375518321990967},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.7852247953414917},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.650589108467102},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6263397932052612},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.5623753070831299},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4511895477771759},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.3708595633506775},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16626888513565063},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.14560359716415405},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.13508164882659912},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.11458718776702881},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0},{"id":"https://openalex.org/C147789679","wikidata":"https://www.wikidata.org/wiki/Q11372","display_name":"Physical chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc53992.2023.10393874","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/smc53992.2023.10393874","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2560023338","https://openalex.org/W2884436604","https://openalex.org/W2962914239","https://openalex.org/W3008985036","https://openalex.org/W3015788359","https://openalex.org/W3033272814","https://openalex.org/W3045672834","https://openalex.org/W3088226460","https://openalex.org/W3120333390","https://openalex.org/W3126335003","https://openalex.org/W3169965180","https://openalex.org/W3176628328","https://openalex.org/W3185556852","https://openalex.org/W4224927203","https://openalex.org/W4295934721","https://openalex.org/W4319216049","https://openalex.org/W4328108640"],"related_works":["https://openalex.org/W2392040637","https://openalex.org/W3085764877","https://openalex.org/W2514414740","https://openalex.org/W3212781313","https://openalex.org/W2377414158","https://openalex.org/W3199615306","https://openalex.org/W77207468","https://openalex.org/W4307725381","https://openalex.org/W124863575","https://openalex.org/W3203147184"],"abstract_inverted_index":{"Accurate":[0],"COVID-19":[1,92],"lesion":[2],"segmentation":[3,208],"is":[4],"vital":[5],"for":[6,222],"diagnosing":[7],"lung":[8],"infections.":[9],"Experiment":[10],"results":[11],"suggest":[12],"that":[13,200],"a":[14,20,34,51,62,111,206,219],"great":[15],"teacher":[16,113,124],"may":[17,215],"not":[18,39],"produce":[19],"brilliant":[21],"student":[22,47,119,144,168,188],"due":[23],"to":[24,85,95,114,166,181],"the":[25,41,56,68,87,108,122,131,139,143,152,172,183,211],"huge":[26],"gap":[27,141],"in":[28,50,128],"contextual":[29],"semantics.":[30],"Also":[31],"studying":[32],"from":[33],"single":[35],"knowledge":[36,49],"domain":[37],"does":[38],"improve":[40],"student's":[42],"learning":[43],"ability.":[44],"To":[45],"help":[46],"understand":[48],"rational":[52],"manner":[53],"and":[54,145,147,160,189],"solve":[55,86],"aforementioned":[57],"issues":[58],"we":[59,150,175,192],"creatively":[60],"design":[61,79],"multi-teacher":[63,146],"distillation":[64,203],"framework":[65,72,204],"based":[66],"on":[67,118,194,210],"CNN-Transformer.":[69],"Our":[70],"proposed":[71,202],"has":[73,125],"three":[74],"main":[75],"benefits":[76],"1)":[77],"We":[78],"GMDiff":[80],"(Generate":[81],"Medical":[82],"Diffusion":[83],"Model)":[84],"scarcity":[88],"problem":[89],"of":[90,110],"high-quality":[91],"medical":[93],"images":[94],"adapt":[96],"few-shot":[97],"learning.":[98,120,169],"2)":[99],"The":[100],"DWD":[101],"(Dynamic":[102],"Weight":[103],"Distribution)":[104],"can":[105,133],"adaptively":[106],"adjusts":[107],"weight":[109],"weak":[112,123],"reduce":[115],"incorrect":[116],"guidance":[117],"When":[121],"enough":[126],"confidence":[127],"their":[129],"decisions":[130],"students":[132],"achieve":[134],"satisfactory":[135],"results.":[136],"3)To":[137],"bridge":[138],"semantic":[140],"between":[142],"facilitate":[148],"interaction":[149],"propose":[151],"MSL":[153],"(Multi-Scale":[154],"Loss)":[155,159,164],"AGL":[156],"(Attention":[157],"Gradient":[158],"EPL":[161],"(Edge":[162],"Pixel":[163],"strategies":[165,174],"supervise":[167],"Before":[170],"utilizing":[171],"above":[173],"adopt":[176],"IPM":[177],"(Information":[178],"Processing":[179],"Module)":[180],"standardize":[182],"feature":[184],"representation":[185],"shared":[186],"by":[187],"teachers.":[190],"Finally":[191],"fine-tune":[193],"local":[195],"details.":[196],"Extensive":[197],"experiments":[198],"show":[199],"our":[201],"achieves":[205],"state-of-the-art":[207],"result":[209],"multi-modality":[212],"dataset.":[213],"It":[214],"be":[216],"regarded":[217],"as":[218],"novel":[220],"baseline":[221],"future":[223],"researches.":[224]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
