{"id":"https://openalex.org/W7160519602","doi":"https://doi.org/10.1016/j.eswa.2026.132710","title":"Hierarchical supervision in DINOv2 training improves generalizability on white blood cell images","display_name":"Hierarchical supervision in DINOv2 training improves generalizability on white blood cell images","publication_year":2026,"publication_date":"2026-05-07","ids":{"openalex":"https://openalex.org/W7160519602","doi":"https://doi.org/10.1016/j.eswa.2026.132710"},"language":"en","primary_location":{"id":"doi:10.1016/j.eswa.2026.132710","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.eswa.2026.132710","pdf_url":null,"source":{"id":"https://openalex.org/S13144211","display_name":"Expert Systems with Applications","issn_l":"0957-4174","issn":["0957-4174","1873-6793"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Expert Systems with Applications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.eswa.2026.132710","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5106680560","display_name":"Manon Chossegros","orcid":"https://orcid.org/0000-0003-1994-8806"},"institutions":[{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Manon Chossegros","raw_affiliation_strings":["Sorbonne Universit\u00e9, France"],"raw_orcid":"https://orcid.org/0000-0003-1994-8806","affiliations":[{"raw_affiliation_string":"Sorbonne Universit\u00e9, France","institution_ids":["https://openalex.org/I39804081"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135577604","display_name":"Sophia Wagner","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sophia Wagner","raw_affiliation_strings":["Harvard Medical School, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard Medical School, France","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135367862","display_name":"Christian Matek","orcid":null},"institutions":[{"id":"https://openalex.org/I4210088053","display_name":"Universit\u00e4tsklinikum Erlangen","ror":"https://ror.org/0030f2a11","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I4210088053"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christian Matek","raw_affiliation_strings":["University of Erlangen Pathology Institute, France"],"raw_orcid":"https://orcid.org/0000-0001-8528-8581","affiliations":[{"raw_affiliation_string":"University of Erlangen Pathology Institute, France","institution_ids":["https://openalex.org/I4210088053"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048758770","display_name":"Daniel Stockholm","orcid":"https://orcid.org/0000-0002-5069-5256"},"institutions":[{"id":"https://openalex.org/I2746051580","display_name":"Universit\u00e9 Paris Sciences et Lettres","ror":"https://ror.org/013cjyk83","country_code":"FR","type":"education","lineage":["https://openalex.org/I2746051580"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Daniel Stockholm","raw_affiliation_strings":["PSL University, France"],"raw_orcid":"https://orcid.org/0000-0002-5069-5256","affiliations":[{"raw_affiliation_string":"PSL University, France","institution_ids":["https://openalex.org/I2746051580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056834851","display_name":"Xavier Tannier","orcid":"https://orcid.org/0000-0002-2452-8868"},"institutions":[{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Xavier Tannier","raw_affiliation_strings":["Sorbonne University, France"],"raw_orcid":"https://orcid.org/0000-0002-2452-8868","affiliations":[{"raw_affiliation_string":"Sorbonne University, France","institution_ids":["https://openalex.org/I39804081"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5135580095","display_name":"Carsten Marr","orcid":null},"institutions":[{"id":"https://openalex.org/I2802821144","display_name":"Center for Environmental Health","ror":"https://ror.org/03k84rm07","country_code":"US","type":"facility","lineage":["https://openalex.org/I2802821144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carsten Marr","raw_affiliation_strings":["Helmholtz Center Munich German Research Center for Environmental Health, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Helmholtz Center Munich German Research Center for Environmental Health, France","institution_ids":["https://openalex.org/I2802821144"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5056834851"],"corresponding_institution_ids":["https://openalex.org/I39804081"],"apc_list":{"value":3220,"currency":"USD","value_usd":3220},"apc_paid":{"value":3220,"currency":"USD","value_usd":3220},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.59155123,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"327","issue":null,"first_page":"132710","last_page":"132710"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.982200026512146,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.982200026512146,"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/T10862","display_name":"AI in cancer detection","score":0.009600000455975533,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.0038999998942017555,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.8521999716758728},{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.6722000241279602},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6697999835014343},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5088000297546387},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4677000045776367},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4675999879837036},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.43639999628067017},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4239000082015991}],"concepts":[{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.8521999716758728},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.6722000241279602},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6697999835014343},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6563000082969666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.599399983882904},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5295000076293945},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5088000297546387},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4677000045776367},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4675999879837036},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.43639999628067017},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4239000082015991},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.42160001397132874},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.37790000438690186},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3695000112056732},{"id":"https://openalex.org/C2778488018","wikidata":"https://www.wikidata.org/wiki/Q42395","display_name":"White blood cell","level":2,"score":0.36719998717308044},{"id":"https://openalex.org/C87345402","wikidata":"https://www.wikidata.org/wiki/Q485202","display_name":"Analytic hierarchy process","level":2,"score":0.35120001435279846},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3375000059604645},{"id":"https://openalex.org/C53059260","wikidata":"https://www.wikidata.org/wiki/Q374758","display_name":"Multilevel model","level":2,"score":0.32670000195503235},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.304500013589859},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.30379998683929443},{"id":"https://openalex.org/C2779466056","wikidata":"https://www.wikidata.org/wiki/Q107630651","display_name":"Time point","level":2,"score":0.3018999993801117},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.29409998655319214},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2904999852180481},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2635999917984009},{"id":"https://openalex.org/C3019917304","wikidata":"https://www.wikidata.org/wiki/Q886518","display_name":"Blood count","level":2,"score":0.26080000400543213}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.eswa.2026.132710","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.eswa.2026.132710","pdf_url":null,"source":{"id":"https://openalex.org/S13144211","display_name":"Expert Systems with Applications","issn_l":"0957-4174","issn":["0957-4174","1873-6793"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Expert Systems with Applications","raw_type":"journal-article"},{"id":"pmh:oai:HAL:hal-05691366v1","is_oa":false,"landing_page_url":"https://hal.science/hal-05691366","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Expert Systems with Applications, 2026, 327, pp.132710. &#x27E8;10.1016/j.eswa.2026.132710&#x27E9;","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1016/j.eswa.2026.132710","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.eswa.2026.132710","pdf_url":null,"source":{"id":"https://openalex.org/S13144211","display_name":"Expert Systems with Applications","issn_l":"0957-4174","issn":["0957-4174","1873-6793"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Expert Systems with Applications","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320330232","display_name":"Sorbonne Universit\u00e9","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1980276039","https://openalex.org/W2336829997","https://openalex.org/W2462007197","https://openalex.org/W2793002108","https://openalex.org/W2986235590","https://openalex.org/W3015930014","https://openalex.org/W3194282450","https://openalex.org/W4207016125","https://openalex.org/W4211259900","https://openalex.org/W4238235930","https://openalex.org/W4324304911","https://openalex.org/W4391483785","https://openalex.org/W4392947521","https://openalex.org/W4400062692","https://openalex.org/W4407780934","https://openalex.org/W4413274536"],"related_works":[],"abstract_inverted_index":{"\u2022":[0,12,22,32,41],"Hierarchical":[1,42],"supervision":[2,43],"in":[3,44,64],"DINOv2":[4,45,70],"improves":[5,47,188],"the":[6,97,143,155,191,201,205,216,220,225,230],"latent":[7,232],"space":[8,233],"for":[9,28],"WBC":[10],"classification.":[11],"Biologically":[13],"informed":[14,107],"hierarchy":[15,108,162],"reduces":[16],"error":[17],"severity":[18],"and":[19,211],"aligns":[20,229],"features.":[21],"The":[23,54],"clustering":[24],"is":[25,60],"improved":[26],"even":[27],"non-leukocytic":[29],"out-of-domain":[30,181,221],"datasets.":[31],"Hierarchy":[33],"supports":[34],"labels":[35],"with":[36,120,132,234],"different":[37],"degrees":[38],"of":[39,57,99,109,135,145,183,190],"precision.":[40],"training":[46],"generalizability":[48],"on":[49,175,204,219],"white":[50,110],"blood":[51,58,79,111,207],"cell":[52,80,112,146,208],"images.":[53],"microscopic":[55],"observation":[56],"cells":[59],"a":[61,105,116,121,139,167],"crucial":[62],"step":[63],"diagnosing":[65],"pathologies":[66],"such":[67],"as":[68,166],"leukemia.":[69],"models":[71],"have":[72],"been":[73],"employed":[74],"to":[75,164,193,238],"extract":[76],"features":[77],"from":[78],"images,":[81],"but":[82],"they":[83,91],"do":[84,90],"not":[85],"include":[86],"biological":[87,235],"knowledge,":[88],"nor":[89],"allow":[92],"multi-granular":[93],"labels.":[94],"To":[95,148],"enhance":[96],"representation":[98],"these":[100],"cells,":[101],"we":[102,153],"propose":[103],"leveraging":[104],"biologically":[106],"types.":[113],"We":[114,171],"train":[115],"DINOv2-based":[117],"foundation":[118],"model":[119,174,192],"semi-supervised":[122],"framework":[123],"that":[124,141],"uses":[125],"hierarchical":[126,157],"supervision.":[127],"It":[128],"enables":[129],"using":[130],"datasets":[131],"varying":[133],"levels":[134],"label":[136,151],"precision":[137],"within":[138],"structure":[140],"represents":[142],"process":[144],"differentiation.":[147],"support":[149],"multi-level":[150],"precision,":[152],"modify":[154],"original":[156],"loss":[158],"function,":[159],"allowing":[160],"any":[161],"level":[163],"serve":[165],"ground":[168],"truth":[169],"class.":[170],"evaluate":[172],"our":[173],"three":[176],"external":[177,209],"datasets,":[178,195,210],"including":[179],"an":[180],"set":[182],"cervical":[184],"cells.":[185],"Our":[186],"approach":[187],"generalization":[189],"new":[194],"improving":[196],"by":[197,212],"1":[198],"percentage":[199,214],"point":[200,215],"balanced":[202,217],"accuracy":[203,218],"two":[206],"2.5":[213],"dataset.":[222],"In":[223],"addition":[224],"proposed":[226],"strategy":[227],"better":[228],"model\u2019s":[231],"properties,":[236],"leading":[237],"more":[239],"acceptable":[240],"misclassifications":[241]},"counts_by_year":[],"updated_date":"2026-07-16T13:24:37.021932","created_date":"2026-05-08T00:00:00"}
