{"id":"https://openalex.org/W4319996358","doi":"https://doi.org/10.1109/tmi.2023.3237183","title":"Reliable Mutual Distillation for Medical Image Segmentation Under Imperfect Annotations","display_name":"Reliable Mutual Distillation for Medical Image Segmentation Under Imperfect Annotations","publication_year":2023,"publication_date":"2023-01-18","ids":{"openalex":"https://openalex.org/W4319996358","doi":"https://doi.org/10.1109/tmi.2023.3237183","pmid":"https://pubmed.ncbi.nlm.nih.gov/37021848"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2023.3237183","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2023.3237183","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003019748","display_name":"Chaowei Fang","orcid":"https://orcid.org/0000-0001-8805-9792"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chaowei Fang","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100391054","display_name":"Qian Wang","orcid":"https://orcid.org/0000-0002-3490-3836"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Wang","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060524512","display_name":"Lechao Cheng","orcid":"https://orcid.org/0000-0002-7546-9052"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lechao Cheng","raw_affiliation_strings":["Zhejiang Laboratory, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang Laboratory, Hangzhou, China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049053722","display_name":"Zhifan Gao","orcid":"https://orcid.org/0000-0002-1576-4439"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhifan Gao","raw_affiliation_strings":["School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030668126","display_name":"Chengwei Pan","orcid":"https://orcid.org/0000-0003-0497-7903"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengwei Pan","raw_affiliation_strings":["Institute of Artificial Intelligence, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103031182","display_name":"Zhen Cao","orcid":"https://orcid.org/0000-0002-3870-1342"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Cao","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019721689","display_name":"Zhaohui Zheng","orcid":"https://orcid.org/0000-0003-3817-0171"},"institutions":[{"id":"https://openalex.org/I4210158926","display_name":"Xijing Hospital","ror":"https://ror.org/05cqe9350","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210158926"]},{"id":"https://openalex.org/I9916479","display_name":"Air Force Medical University","ror":"https://ror.org/00ms48f15","country_code":"CN","type":"education","lineage":["https://openalex.org/I9916479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaohui Zheng","raw_affiliation_strings":["Xijing Hospital, The Fourth Military Medical University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"Xijing Hospital, The Fourth Military Medical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I9916479","https://openalex.org/I4210158926"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101954574","display_name":"Dingwen Zhang","orcid":"https://orcid.org/0000-0001-8369-8886"},"institutions":[{"id":"https://openalex.org/I4210158926","display_name":"Xijing Hospital","ror":"https://ror.org/05cqe9350","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210158926"]},{"id":"https://openalex.org/I9916479","display_name":"Air Force Medical University","ror":"https://ror.org/00ms48f15","country_code":"CN","type":"education","lineage":["https://openalex.org/I9916479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dingwen Zhang","raw_affiliation_strings":["Xijing Hospital, The Fourth Military Medical University, Xi&#x2019;an, China","Hefei Comprehensive National Science Center, Institute of Artificial Intelligence, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Xijing Hospital, The Fourth Military Medical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I9916479","https://openalex.org/I4210158926"]},{"raw_affiliation_string":"Hefei Comprehensive National Science Center, Institute of Artificial Intelligence, Hefei, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5003019748"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":9.6452,"has_fulltext":false,"cited_by_count":80,"citation_normalized_percentile":{"value":0.98738117,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"42","issue":"6","first_page":"1720","last_page":"1734"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9991999864578247,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9988999962806702,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9955000281333923,"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":0.8671891689300537},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6738771796226501},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6272687315940857},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5212045907974243},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5160379409790039},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.513818085193634},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47461429238319397},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4717206358909607},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.47064298391342163},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.44654232263565063},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4376397132873535},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.394988089799881},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3947037160396576}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8671891689300537},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6738771796226501},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6272687315940857},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5212045907974243},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5160379409790039},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.513818085193634},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47461429238319397},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4717206358909607},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.47064298391342163},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.44654232263565063},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4376397132873535},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.394988089799881},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3947037160396576},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","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},{"descriptor_ui":"D057168","descriptor_name":"Distillation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057168","descriptor_name":"Distillation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057168","descriptor_name":"Distillation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tmi.2023.3237183","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2023.3237183","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:37021848","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37021848","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}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.47999998927116394,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G2513888872","display_name":null,"funder_award_id":"62106235","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2810332001","display_name":null,"funder_award_id":"62272468","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3108167750","display_name":null,"funder_award_id":"62003256","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3444880253","display_name":null,"funder_award_id":"LQ21F020003","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G3642234580","display_name":null,"funder_award_id":"62104176","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6408364431","display_name":null,"funder_award_id":"U21B2048","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"},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W4919037","https://openalex.org/W1821462560","https://openalex.org/W1866935739","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1986649315","https://openalex.org/W2095705004","https://openalex.org/W2194775991","https://openalex.org/W2253429366","https://openalex.org/W2566079294","https://openalex.org/W2602106906","https://openalex.org/W2618237340","https://openalex.org/W2620998106","https://openalex.org/W2682189153","https://openalex.org/W2804047627","https://openalex.org/W2884436604","https://openalex.org/W2885593519","https://openalex.org/W2907750714","https://openalex.org/W2952634764","https://openalex.org/W2962914239","https://openalex.org/W2963096987","https://openalex.org/W2963446712","https://openalex.org/W2963735582","https://openalex.org/W2964227007","https://openalex.org/W2964292098","https://openalex.org/W2966397396","https://openalex.org/W2979901318","https://openalex.org/W2984666090","https://openalex.org/W2990231018","https://openalex.org/W2996290406","https://openalex.org/W2997941347","https://openalex.org/W2998544007","https://openalex.org/W3001197829","https://openalex.org/W3014974815","https://openalex.org/W3015788359","https://openalex.org/W3021472582","https://openalex.org/W3033272814","https://openalex.org/W3034185248","https://openalex.org/W3039366696","https://openalex.org/W3044256341","https://openalex.org/W3046830682","https://openalex.org/W3087642760","https://openalex.org/W3091211922","https://openalex.org/W3108860939","https://openalex.org/W3110796009","https://openalex.org/W3112701542","https://openalex.org/W3117854388","https://openalex.org/W3119458123","https://openalex.org/W3157723138","https://openalex.org/W3162475669","https://openalex.org/W3188582951","https://openalex.org/W3202865535","https://openalex.org/W3203148062","https://openalex.org/W3203488660","https://openalex.org/W3204497690","https://openalex.org/W4226402304","https://openalex.org/W4297791576","https://openalex.org/W6600213771","https://openalex.org/W6638523607","https://openalex.org/W6639056814","https://openalex.org/W6639824700","https://openalex.org/W6674330103","https://openalex.org/W6751647823","https://openalex.org/W6752558437","https://openalex.org/W6754484989","https://openalex.org/W6769679973","https://openalex.org/W6772311520","https://openalex.org/W6773005947","https://openalex.org/W6776411772","https://openalex.org/W6776492765","https://openalex.org/W6782070623","https://openalex.org/W6811385965"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2358755282","https://openalex.org/W2625833328","https://openalex.org/W1533177136","https://openalex.org/W4380994516","https://openalex.org/W2251519152"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2],"(CNNs)":[3],"have":[4],"made":[5],"enormous":[6],"progress":[7],"in":[8,76,86],"medical":[9],"image":[10],"segmentation.":[11],"The":[12,28],"learning":[13,63,74],"of":[14,22,30,64,93,116,123,131,155,171,182],"CNNs":[15],"is":[16,96,134,149,221],"dependent":[17],"on":[18,176,207],"a":[19,71],"large":[20],"amount":[21],"training":[23,103,125],"data":[24,31,104,163],"with":[25,140,191,216],"fine":[26],"annotations.":[27,88],"workload":[29],"labeling":[32],"can":[33,199],"be":[34],"significantly":[35],"relieved":[36],"via":[37],"collecting":[38],"imperfect":[39],"annotations":[40,190,215],"which":[41,52,77],"only":[42],"match":[43],"the":[44,57,62,90,106,113,124,127,137,153,156,169,180,208],"underlying":[45],"ground":[46],"truths":[47],"coarsely.":[48],"However,":[49],"label":[50,84,117],"noises":[51,85,118],"are":[53],"systematically":[54],"introduced":[55],"by":[56,98,203],"annotation":[58],"protocols,":[59],"severely":[60],"hinders":[61],"CNN-based":[65],"segmentation":[66,79,211],"models.":[67],"Hence,":[68],"we":[69,160],"devise":[70],"novel":[72],"collaborative":[73],"framework":[75],"two":[78,94,177],"models":[80,95],"cooperate":[81],"to":[82,110,167],"combat":[83],"coarse":[87],"First,":[89],"complementary":[91],"knowledge":[92,130],"explored":[97],"making":[99],"one":[100],"model":[101,133,139,165],"clean":[102],"for":[105,151],"other":[107,138],"model.":[108],"Secondly,":[109],"further":[111],"alleviate":[112],"negative":[114],"impact":[115],"and":[119,164],"make":[120],"sufficient":[121],"usage":[122,170],"data,":[126],"specific":[128],"reliable":[129,172],"each":[132],"distilled":[135,157],"into":[136],"augmentation-based":[141],"consistency":[142],"constraints.":[143],"A":[144],"reliability-aware":[145],"sample":[146],"selection":[147],"strategy":[148],"incorporated":[150],"guaranteeing":[152],"quality":[154],"knowledge.":[158,173],"Moreover,":[159],"employ":[161],"joint":[162],"augmentations":[166],"expand":[168],"Extensive":[174],"experiments":[175],"benchmarks":[178],"showcase":[179],"superiority":[181],"our":[183,197],"proposed":[184],"method":[185],"against":[186],"existing":[187,201],"methods":[188,202],"under":[189,214],"different":[192],"noise":[193,218],"levels.":[194],"For":[195],"example,":[196],"approach":[198],"improve":[200],"nearly":[204],"3%":[205],"DSC":[206],"lung":[209],"lesion":[210],"dataset":[212],"LIDC-IDRI":[213],"80%":[217],"ratio.":[219],"Code":[220],"available":[222],"at:":[223],"https://github.com/Amber-Believe/ReliableMutualDistillation.":[224]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":29},{"year":2024,"cited_by_count":38},{"year":2023,"cited_by_count":8}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
