{"id":"https://openalex.org/W4406188143","doi":"https://doi.org/10.1186/s42492-024-00181-8","title":"Advancing breast cancer diagnosis: token vision transformers for faster and accurate classification of histopathology images","display_name":"Advancing breast cancer diagnosis: token vision transformers for faster and accurate classification of histopathology images","publication_year":2025,"publication_date":"2025-01-08","ids":{"openalex":"https://openalex.org/W4406188143","doi":"https://doi.org/10.1186/s42492-024-00181-8","pmid":"https://pubmed.ncbi.nlm.nih.gov/39775534"},"language":"en","primary_location":{"id":"doi:10.1186/s42492-024-00181-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42492-024-00181-8","pdf_url":"https://vciba.springeropen.com/counter/pdf/10.1186/s42492-024-00181-8","source":{"id":"https://openalex.org/S3035464634","display_name":"Visual Computing for Industry Biomedicine and Art","issn_l":"2096-496X","issn":["2096-496X","2524-4442"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Visual Computing for Industry, Biomedicine, and Art","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://vciba.springeropen.com/counter/pdf/10.1186/s42492-024-00181-8","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5094179120","display_name":"Mouhamed Laid Abimouloud","orcid":"https://orcid.org/0009-0009-1841-9305"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":true,"raw_author_name":"Mouhamed Laid Abimouloud","raw_affiliation_strings":["Advanced Technologies for Environment and Smart Cities (ATES Unit), Sfax University, Sfax, Tunisia. mohamed.abimouloud@enis.tn","National Engineering School of Sfax, University of Sfax, Sfax, Tunisia. mohamed.abimouloud@enis.tn","National Engineering School of Sfax, University of Sfax, Sfax, Tunisia","Advanced Technologies for Environment and Smart Cities (ATES Unit), Sfax University, Sfax, Tunisia"],"affiliations":[{"raw_affiliation_string":"Advanced Technologies for Environment and Smart Cities (ATES Unit), Sfax University, Sfax, Tunisia. mohamed.abimouloud@enis.tn","institution_ids":["https://openalex.org/I142899784"]},{"raw_affiliation_string":"National Engineering School of Sfax, University of Sfax, Sfax, Tunisia. mohamed.abimouloud@enis.tn","institution_ids":["https://openalex.org/I142899784"]},{"raw_affiliation_string":"National Engineering School of Sfax, University of Sfax, Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]},{"raw_affiliation_string":"Advanced Technologies for Environment and Smart Cities (ATES Unit), Sfax University, Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046587201","display_name":"Khaled Bensid","orcid":"https://orcid.org/0000-0001-8502-907X"},"institutions":[{"id":"https://openalex.org/I114564095","display_name":"University of Ouargla","ror":"https://ror.org/05amrd548","country_code":"DZ","type":"education","lineage":["https://openalex.org/I114564095"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Khaled Bensid","raw_affiliation_strings":["Laboratory of Electrical Engineering (LAGE), University of KASDI Merbah Ouargla, 30000, Ouargla, Algeria"],"affiliations":[{"raw_affiliation_string":"Laboratory of Electrical Engineering (LAGE), University of KASDI Merbah Ouargla, 30000, Ouargla, Algeria","institution_ids":["https://openalex.org/I114564095"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052764348","display_name":"Mohamed Elleuch","orcid":"https://orcid.org/0000-0003-4702-7692"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]},{"id":"https://openalex.org/I83259278","display_name":"Manouba University","ror":"https://ror.org/0503ejf32","country_code":"TN","type":"education","lineage":["https://openalex.org/I83259278"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Mohamed Elleuch","raw_affiliation_strings":["Advanced Technologies for Environment and Smart Cities (ATES Unit), Sfax University, Sfax, Tunisia","National School of Computer Science (ENSI), University of Manouba, Manouba, Tunisia"],"affiliations":[{"raw_affiliation_string":"Advanced Technologies for Environment and Smart Cities (ATES Unit), Sfax University, Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]},{"raw_affiliation_string":"National School of Computer Science (ENSI), University of Manouba, Manouba, Tunisia","institution_ids":["https://openalex.org/I83259278"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003627659","display_name":"Mohamed Ben Ammar","orcid":"https://orcid.org/0000-0001-8990-3924"},"institutions":[{"id":"https://openalex.org/I118590987","display_name":"Northern Border University","ror":"https://ror.org/03j9tzj20","country_code":"SA","type":"education","lineage":["https://openalex.org/I118590987"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Mohamed Ben Ammar","raw_affiliation_strings":["Department of Information Systems, Faculty of Computing and Information Technology, Northern Border University, Rafha, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"Department of Information Systems, Faculty of Computing and Information Technology, Northern Border University, Rafha, Saudi Arabia","institution_ids":["https://openalex.org/I118590987"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004803772","display_name":"Monji Kherallah","orcid":"https://orcid.org/0000-0002-4549-1005"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Monji Kherallah","raw_affiliation_strings":["Advanced Technologies for Environment and Smart Cities (ATES Unit), Sfax University, Sfax, Tunisia","Faculty of Sciences, Sfax, Tunisia"],"affiliations":[{"raw_affiliation_string":"Advanced Technologies for Environment and Smart Cities (ATES Unit), Sfax University, Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]},{"raw_affiliation_string":"Faculty of Sciences, Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5094179120"],"corresponding_institution_ids":["https://openalex.org/I142899784"],"apc_list":null,"apc_paid":null,"fwci":45.4825,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.99758871,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"8","issue":"1","first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":1.0,"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":1.0,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9952999949455261,"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":0.9890999794006348,"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/computer-science","display_name":"Computer science","score":0.8199838399887085},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6711399555206299},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.645446240901947},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.605252742767334},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5436408519744873},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47884678840637207},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4228765368461609},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33770906925201416}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8199838399887085},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6711399555206299},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.645446240901947},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.605252742767334},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5436408519744873},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47884678840637207},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4228765368461609},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33770906925201416},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1186/s42492-024-00181-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42492-024-00181-8","pdf_url":"https://vciba.springeropen.com/counter/pdf/10.1186/s42492-024-00181-8","source":{"id":"https://openalex.org/S3035464634","display_name":"Visual Computing for Industry Biomedicine and Art","issn_l":"2096-496X","issn":["2096-496X","2524-4442"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Visual Computing for Industry, Biomedicine, and Art","raw_type":"journal-article"},{"id":"pmid:39775534","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39775534","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":"Visual computing for industry, biomedicine, and art","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11711433","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11711433","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11711433/pdf/42492_2024_Article_181.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Vis Comput Ind Biomed Art","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:785fe16be0b3406189c8b1b0c2b23adf","is_oa":true,"landing_page_url":"https://doaj.org/article/785fe16be0b3406189c8b1b0c2b23adf","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Visual Computing for Industry, Biomedicine, and Art, Vol 8, Iss 1, Pp 1-27 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s42492-024-00181-8","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42492-024-00181-8","pdf_url":"https://vciba.springeropen.com/counter/pdf/10.1186/s42492-024-00181-8","source":{"id":"https://openalex.org/S3035464634","display_name":"Visual Computing for Industry Biomedicine and Art","issn_l":"2096-496X","issn":["2096-496X","2524-4442"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Visual Computing for Industry, Biomedicine, and Art","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.6600000262260437,"display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G5791967564","display_name":null,"funder_award_id":"NBU-FFR-2024-","funder_id":"https://openalex.org/F4320328654","funder_display_name":"Northern Border University"}],"funders":[{"id":"https://openalex.org/F4320328654","display_name":"Northern Border University","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4406188143.pdf","grobid_xml":"https://content.openalex.org/works/W4406188143.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W1965451568","https://openalex.org/W1990082725","https://openalex.org/W2344480160","https://openalex.org/W2772723798","https://openalex.org/W2913559493","https://openalex.org/W2944016032","https://openalex.org/W2944707525","https://openalex.org/W3035161717","https://openalex.org/W3046874697","https://openalex.org/W3081442134","https://openalex.org/W3084893494","https://openalex.org/W3094502228","https://openalex.org/W3121336612","https://openalex.org/W3139587317","https://openalex.org/W3139773203","https://openalex.org/W3150212014","https://openalex.org/W3159778524","https://openalex.org/W3163306278","https://openalex.org/W3189420316","https://openalex.org/W3193873731","https://openalex.org/W3195237310","https://openalex.org/W3202053489","https://openalex.org/W4206462383","https://openalex.org/W4207032074","https://openalex.org/W4211169133","https://openalex.org/W4220768105","https://openalex.org/W4226345037","https://openalex.org/W4229062925","https://openalex.org/W4283809036","https://openalex.org/W4285661751","https://openalex.org/W4286910290","https://openalex.org/W4293163051","https://openalex.org/W4295795848","https://openalex.org/W4308333450","https://openalex.org/W4309585077","https://openalex.org/W4312847199","https://openalex.org/W4313577028","https://openalex.org/W4313583499","https://openalex.org/W4318478374","https://openalex.org/W4319319433","https://openalex.org/W4322616751","https://openalex.org/W4375947229","https://openalex.org/W4387376188","https://openalex.org/W4389977645","https://openalex.org/W4400303610"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W4390516098","https://openalex.org/W4391621807","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W4380075502"],"abstract_inverted_index":{"The":[0,163,272,312],"vision":[1],"transformer":[2,145,230],"(ViT)":[3],"architecture,":[4,39],"with":[5,117,244,285],"its":[6,25],"attention":[7,12,181],"mechanism":[8,165],"based":[9],"on":[10,237],"multi-head":[11],"layers,":[13,185],"has":[14],"been":[15],"widely":[16],"adopted":[17],"in":[18,27,52,72,202,227,309],"various":[19,265],"computer-aided":[20],"diagnosis":[21],"tasks":[22],"due":[23],"to":[24,89,110,147,194,218],"effectiveness":[26],"processing":[28],"medical":[29,54],"image":[30,77],"information.":[31],"ViTs":[32],"are":[33,82],"notably":[34],"recognized":[35],"for":[36,46,154,255,278,283,305],"their":[37],"complex":[38],"which":[40],"requires":[41],"high-performance":[42],"GPUs":[43],"or":[44],"CPUs":[45],"efficient":[47],"model":[48,177,207,236,273],"training":[49,119],"and":[50,85,104,114,121,143,156,171,222,246,258,281,290],"deployment":[51],"real-world":[53],"diagnostic":[55],"devices.":[56],"This":[57,67,106],"renders":[58],"them":[59,217],"more":[60],"intricate":[61],"than":[62],"convolutional":[63,141,184],"neural":[64],"networks":[65],"(CNNs).":[66],"difficulty":[68],"is":[69,166,315],"also":[70],"challenging":[71],"the":[73,80,100,126,169,175,187,196,205,212,234,238,297],"context":[74],"of":[75,102,128,137,189,198,260,276,288,299],"histopathology":[76],"analysis,":[78],"where":[79],"images":[81,193],"both":[83,256],"limited":[84],"complex.":[86],"In":[87],"response":[88],"these":[90],"challenges,":[91],"this":[92],"study":[93],"proposes":[94],"a":[95],"TokenMixer":[96,164,235],"hybrid-architecture":[97],"that":[98],"combines":[99],"strengths":[101],"CNNs":[103],"ViTs.":[105],"hybrid":[107,301],"architecture":[108,304],"aims":[109],"enhance":[111],"feature":[112,220],"extraction":[113,188],"classification":[115,280,308],"accuracy":[116],"shorter":[118],"time":[120],"fewer":[122],"parameters":[123],"by":[124,168],"minimizing":[125],"number":[127,197],"input":[129,138,192,199,214],"patches":[130,139,149,190,200,226],"employed":[131],"during":[132],"training,":[133],"while":[134],"incorporating":[135],"tokenization":[136],"using":[140,183],"layers":[142,146,153],"encoder":[144,229],"process":[148],"across":[150,264],"all":[151,224],"network":[152],"fast":[155],"accurate":[157],"breast":[158,261],"cancer":[159,262],"tumor":[160,307],"subtype":[161],"classification.":[162],"inspired":[167],"ConvMixer":[170,176],"TokenLearner":[172,206],"models.":[173],"First,":[174],"dynamically":[178],"generates":[179],"spatial":[180],"maps":[182],"enabling":[186],"from":[191,211],"minimize":[195],"used":[201],"training.":[203],"Second,":[204],"extracts":[208],"relevant":[209],"regions":[210],"selected":[213],"patches,":[215],"tokenizes":[216],"improve":[219],"extraction,":[221],"trains":[223],"tokenized":[225],"an":[228],"network.":[231],"We":[232],"evaluated":[233],"BreakHis":[239],"public":[240],"dataset,":[241],"comparing":[242],"it":[243],"ViT-based":[245],"other":[247],"state-of-the-art":[248],"methods.":[249],"Our":[250],"approach":[251],"achieved":[252],"impressive":[253],"results":[254,295],"binary":[257,279],"multi-classification":[259],"subtypes":[263],"magnification":[266],"levels":[267],"(40\u00d7,":[268],"100\u00d7,":[269],"200\u00d7,":[270],"400\u00d7).":[271],"demonstrated":[274],"accuracies":[275],"97.02%":[277],"93.29%":[282],"multi-classification,":[284],"decision":[286],"times":[287],"391.71":[289],"1173.56":[291],"s,":[292],"respectively.":[293],"These":[294],"highlight":[296],"potential":[298],"our":[300],"deep":[302],"ViT-CNN":[303],"advancing":[306],"histopathological":[310],"images.":[311],"source":[313],"code":[314],"accessible:":[316],"https://github.com/abimouloud/TokenMixer":[317],".":[318]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":12}],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2025-10-10T00:00:00"}
