{"id":"https://openalex.org/W4387422491","doi":"https://doi.org/10.1007/978-3-031-44917-8_25","title":"Large-Scale Pretraining on Pathological Images for Fine-Tuning of Small Pathological Benchmarks","display_name":"Large-Scale Pretraining on Pathological Images for Fine-Tuning of Small Pathological Benchmarks","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4387422491","doi":"https://doi.org/10.1007/978-3-031-44917-8_25"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-031-44917-8_25","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-44917-8_25","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1007/978-3-031-44917-8_25","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113018177","display_name":"Masakata Kawai","orcid":null},"institutions":[{"id":"https://openalex.org/I66906201","display_name":"University of Yamanashi","ror":"https://ror.org/059x21724","country_code":"JP","type":"education","lineage":["https://openalex.org/I66906201"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Masakata Kawai","raw_affiliation_strings":["Department of Pathology, University of Yamanashi, Yamanashi, Japan"],"raw_orcid":"https://orcid.org/0000-0003-1106-239X","affiliations":[{"raw_affiliation_string":"Department of Pathology, University of Yamanashi, Yamanashi, Japan","institution_ids":["https://openalex.org/I66906201"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031019696","display_name":"Noriaki Ota","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Noriaki Ota","raw_affiliation_strings":["Systems Research and Development Center, Technology Bureau, NS Solutions Corp, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Systems Research and Development Center, Technology Bureau, NS Solutions Corp, Tokyo, Japan","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036720608","display_name":"Shinsuke Yamaoka","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shinsuke Yamaoka","raw_affiliation_strings":["Systems Research and Development Center, Technology Bureau, NS Solutions Corp, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Systems Research and Development Center, Technology Bureau, NS Solutions Corp, Tokyo, Japan","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5113018177"],"corresponding_institution_ids":["https://openalex.org/I66906201"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":{"value":5000,"currency":"EUR","value_usd":5392},"fwci":3.6417,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.94118638,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"257","last_page":"267"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9994999766349792,"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/T10862","display_name":"AI in cancer detection","score":0.9994999766349792,"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":0.9994999766349792,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.984499990940094,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.853278636932373},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7651571035385132},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7421228885650635},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6499083042144775},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6190181970596313},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5241644382476807},{"id":"https://openalex.org/keywords/magnification","display_name":"Magnification","score":0.49286341667175293},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4816955029964447},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39247509837150574},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.050812333822250366}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.853278636932373},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7651571035385132},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7421228885650635},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6499083042144775},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6190181970596313},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5241644382476807},{"id":"https://openalex.org/C4144372","wikidata":"https://www.wikidata.org/wiki/Q675287","display_name":"Magnification","level":2,"score":0.49286341667175293},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4816955029964447},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39247509837150574},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.050812333822250366},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-031-44917-8_25","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-44917-8_25","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.1007/978-3-031-44917-8_25","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-44917-8_25","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2117539524","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2302255633","https://openalex.org/W2581082771","https://openalex.org/W2760946358","https://openalex.org/W2772723798","https://openalex.org/W2806857275","https://openalex.org/W2948930564","https://openalex.org/W2963341956","https://openalex.org/W3005680577","https://openalex.org/W3008526508","https://openalex.org/W3035060554","https://openalex.org/W3035524453","https://openalex.org/W3036982689","https://openalex.org/W3037083567","https://openalex.org/W3097217077","https://openalex.org/W3135367836","https://openalex.org/W3145450063","https://openalex.org/W3159302505","https://openalex.org/W3159481202","https://openalex.org/W3186679119","https://openalex.org/W4205900565","https://openalex.org/W4207066074","https://openalex.org/W4214670085","https://openalex.org/W4225323055","https://openalex.org/W4250482878","https://openalex.org/W4281254305","https://openalex.org/W4281789486","https://openalex.org/W4312204014","https://openalex.org/W4312468136","https://openalex.org/W6679338098","https://openalex.org/W6931259419"],"related_works":["https://openalex.org/W4206357785","https://openalex.org/W3192840557","https://openalex.org/W4281381188","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3023427754","https://openalex.org/W4315434538","https://openalex.org/W4375928479","https://openalex.org/W3131673289","https://openalex.org/W3198847674"],"abstract_inverted_index":{"Pretraining":[0],"a":[1,10,61],"deep":[2,88],"learning":[3,89,97],"model":[4,16],"on":[5,17,101,119,128,140,174],"large":[6,22,44,55,77],"image":[7,74],"datasets":[8,37,83,104],"is":[9,24,50,57],"standard":[11],"step":[12],"before":[13],"fine-tuning":[14],"the":[15,31,43,54,102,145,150,155],"small":[18,32,65,82,103],"targeted":[19],"datasets.":[20,66],"The":[21],"dataset":[23,33,56],"usually":[25],"general":[26],"images":[27],"(e.g.":[28],"imagenet2012)":[29],"while":[30],"can":[34],"be":[35],"specialized":[36,58],"that":[38],"have":[39],"different":[40],"distributions":[41],"from":[42],"dataset.":[45],"However,":[46],"this":[47],"\u201clarge-to-small\u201d":[48],"strategy":[49],"not":[51],"well-validated":[52],"when":[53,126],"and":[59,72,79,85,95,99,108,117,135,148,162,172],"has":[60],"similar":[62],"distribution":[63],"to":[64],"We":[67,164],"newly":[68],"compiled":[69],"three":[70],"hematoxylin":[71],"eosin-stained":[73],"datasets,":[75],"one":[76],"(PTCGA200)":[78],"two":[80],"magnification-adjusted":[81],"(PCam200":[84],"segPANDA200).":[86],"Major":[87],"models":[90,169],"were":[91],"trained":[92],"with":[93,114,142],"supervised":[94,166],"self-supervised":[96],"methods":[98],"fine-tuned":[100,127],"for":[105,154],"tumor":[106],"classification":[107],"tissue":[109,156],"segmentation":[110,157],"benchmarks.":[111,179],"ResNet50":[112,138,153],"pretrained":[113,139],"MoCov2,":[115],"SimCLR,":[116],"BYOL":[118],"PTCGA200":[120,129,141,175],"was":[121,149],"better":[122],"than":[123],"imagenet2012":[124],"pretraining":[125],"(accuracy":[130],"of":[131,160],"83.94%,":[132],"86.41%,":[133],"84.91%,":[134],"82.72%,":[136],"respectively).":[137],"MoCov2":[143],"exceeded":[144],"COCOtrain2017-pretrained":[146],"baseline":[147],"best":[151],"in":[152],"benchmark":[158],"(mIoU":[159],"63.53%":[161],"63.22%).":[163],"found":[165],"re-training":[167],"imagenet-pretrained":[168],"(ResNet50,":[170],"BiT-M-R50x1,":[171],"ViT-S/16)":[173],"often":[176],"improved":[177],"downstream":[178]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}