{"id":"https://openalex.org/W4389363370","doi":"https://doi.org/10.48550/arxiv.2312.01099","title":"Rethinking Multiple Instance Learning for Whole Slide Image Classification: A Bag-Level Classifier is a Good Instance-Level Teacher","display_name":"Rethinking Multiple Instance Learning for Whole Slide Image Classification: A Bag-Level Classifier is a Good Instance-Level Teacher","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4389363370","doi":"https://doi.org/10.48550/arxiv.2312.01099"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2312.01099","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/2312.01099","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100701040","display_name":"Hongyi Wang","orcid":"https://orcid.org/0000-0003-4389-5644"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Hongyi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100536925","display_name":"Luyang Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Luyang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080544783","display_name":"Fang Wang","orcid":"https://orcid.org/0000-0001-8752-8139"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Fang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057181928","display_name":"Ruofeng Tong","orcid":"https://orcid.org/0000-0002-8167-5354"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tong, Ruofeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044216245","display_name":"Yen\u2010Wei Chen","orcid":"https://orcid.org/0000-0002-5952-0188"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yen-Wei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057452864","display_name":"Hongjie Hu","orcid":"https://orcid.org/0000-0002-9859-5860"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Hongjie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090814258","display_name":"Lanfen Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Lanfen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100353596","display_name":"Hao Chen","orcid":"https://orcid.org/0000-0002-8400-3780"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Hao","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":65},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9983,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9983,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9953,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.995,"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":[],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.871776},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7630442},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6203137},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6183358},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49549925},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45534003}],"mesh":[],"locations_count":3,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2312.01099","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2312.01099","pdf_url":"http://arxiv.org/pdf/2312.01099","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2312.01099","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2312.01099","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"display_name":"Quality education","id":"https://metadata.un.org/sdg/4","score":0.79}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4306674287","https://openalex.org/W4283697347","https://openalex.org/W3170094116","https://openalex.org/W3107602296","https://openalex.org/W3046775127","https://openalex.org/W2961085424","https://openalex.org/W2033914206"],"abstract_inverted_index":{"Multiple":[0,106],"Instance":[1,107],"Learning":[2,108],"(MIL)":[3],"has":[4],"demonstrated":[5],"promise":[6],"in":[7,70,152,185],"Whole":[8],"Slide":[9],"Image":[10],"(WSI)":[11],"classification.":[12],"However,":[13],"a":[14,34,38,44,58,71,89,94,119,156,176],"major":[15],"challenge":[16],"persists":[17],"due":[18],"to":[19,78,110,128,139,155,179,189,203],"the":[20,53,74,112,115,125,130,136,141,161,182,186,191,205,219],"high":[21],"computational":[22],"cost":[23],"associated":[24],"with":[25],"processing":[26],"these":[27],"gigapixel":[28],"images.":[29],"Existing":[30],"methods":[31],"generally":[32],"adopt":[33],"two-stage":[35],"approach,":[36],"comprising":[37],"non-learnable":[39],"feature":[40,60],"embedding":[41],"stage":[42],"and":[43,114,168],"classifier":[45,91,117,138,159,188],"training":[46],"stage.":[47],"Though":[48],"it":[49],"can":[50,92,147],"greatly":[51],"reduce":[52],"memory":[54],"consumption":[55],"by":[56,134],"using":[57],"fixed":[59],"embedder":[61,113,127,146,171,193],"pre-trained":[62],"on":[63,99,199],"other":[64],"domains,":[65],"such":[66],"scheme":[67],"also":[68,174],"results":[69,211],"disparity":[72],"between":[73],"two":[75],"stages,":[76],"leading":[77,154],"suboptimal":[79],"classification":[80],"accuracy.":[81],"To":[82,164],"address":[83],"this":[84,100],"issue,":[85],"we":[86,102,173],"propose":[87],"that":[88,214],"bag-level":[90],"be":[93],"good":[95],"instance-level":[96,192],"teacher.":[97],"Based":[98],"idea,":[101],"design":[103],"Iteratively":[104],"Coupled":[105],"(ICMIL)":[109],"couple":[111],"bag":[116,131,137,187],"at":[118],"low":[120],"cost.":[121],"ICMIL":[122],"initially":[123],"fix":[124],"patch":[126,142],"train":[129],"classifier,":[132],"followed":[133],"fixing":[135],"fine-tune":[140],"embedder.":[143],"The":[144,209,228],"refined":[145],"then":[148],"generate":[149],"better":[150],"representations":[151],"return,":[153],"more":[157,166,169],"accurate":[158],"for":[160],"next":[162],"iteration.":[163],"realize":[165],"flexible":[167],"effective":[170],"fine-tuning,":[172],"introduce":[175],"teacher-student":[177],"framework":[178],"efficiently":[180],"distill":[181],"category":[183],"knowledge":[184],"help":[190],"fine-tuning.":[194],"Thorough":[195],"experiments":[196],"were":[197],"conducted":[198],"four":[200],"distinct":[201],"datasets":[202],"validate":[204],"effectiveness":[206],"of":[207,221],"ICMIL.":[208],"experimental":[210],"consistently":[212],"demonstrate":[213],"our":[215],"method":[216],"significantly":[217],"improves":[218],"performance":[220],"existing":[222],"MIL":[223],"backbones,":[224],"achieving":[225],"state-of-the-art":[226],"results.":[227],"code":[229],"is":[230],"available":[231],"at:":[232],"https://github.com/Dootmaan/ICMIL/tree/confidence_based":[233]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4389363370","counts_by_year":[],"updated_date":"2025-04-09T15:51:15.573129","created_date":"2023-12-06"}