{"id":"https://openalex.org/W4401753183","doi":"https://doi.org/10.1109/isbi56570.2024.10635578","title":"MV-Swin-T: Mammogram Classification with Multi-View Swin Transformer","display_name":"MV-Swin-T: Mammogram Classification with Multi-View Swin Transformer","publication_year":2024,"publication_date":"2024-05-27","ids":{"openalex":"https://openalex.org/W4401753183","doi":"https://doi.org/10.1109/isbi56570.2024.10635578","pmid":"https://pubmed.ncbi.nlm.nih.gov/39371472"},"language":"en","primary_location":{"id":"doi:10.1109/isbi56570.2024.10635578","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi56570.2024.10635578","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11450559/pdf/nihms-1972093.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036868602","display_name":"Sushmita Sarker","orcid":"https://orcid.org/0000-0003-0390-3099"},"institutions":[{"id":"https://openalex.org/I134113660","display_name":"University of Nevada, Reno","ror":"https://ror.org/01keh0577","country_code":"US","type":"education","lineage":["https://openalex.org/I134113660"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sushmita Sarker","raw_affiliation_strings":["University of Nevada,Department of Computer Science and Engineering,Reno,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Nevada,Department of Computer Science and Engineering,Reno,USA","institution_ids":["https://openalex.org/I134113660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001049098","display_name":"Prithul Sarker","orcid":"https://orcid.org/0000-0002-6290-5484"},"institutions":[{"id":"https://openalex.org/I134113660","display_name":"University of Nevada, Reno","ror":"https://ror.org/01keh0577","country_code":"US","type":"education","lineage":["https://openalex.org/I134113660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Prithul Sarker","raw_affiliation_strings":["University of Nevada,Department of Computer Science and Engineering,Reno,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Nevada,Department of Computer Science and Engineering,Reno,USA","institution_ids":["https://openalex.org/I134113660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016844866","display_name":"George Bebis","orcid":"https://orcid.org/0000-0003-0966-6063"},"institutions":[{"id":"https://openalex.org/I134113660","display_name":"University of Nevada, Reno","ror":"https://ror.org/01keh0577","country_code":"US","type":"education","lineage":["https://openalex.org/I134113660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George Bebis","raw_affiliation_strings":["University of Nevada,Department of Computer Science and Engineering,Reno,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Nevada,Department of Computer Science and Engineering,Reno,USA","institution_ids":["https://openalex.org/I134113660"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017952778","display_name":"Alireza Tavakkoli","orcid":"https://orcid.org/0000-0001-9460-1269"},"institutions":[{"id":"https://openalex.org/I134113660","display_name":"University of Nevada, Reno","ror":"https://ror.org/01keh0577","country_code":"US","type":"education","lineage":["https://openalex.org/I134113660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alireza Tavakkoli","raw_affiliation_strings":["University of Nevada,Department of Computer Science and Engineering,Reno,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Nevada,Department of Computer Science and Engineering,Reno,USA","institution_ids":["https://openalex.org/I134113660"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5036868602"],"corresponding_institution_ids":["https://openalex.org/I134113660"],"apc_list":null,"apc_paid":null,"fwci":8.318,"has_fulltext":true,"cited_by_count":26,"citation_normalized_percentile":{"value":0.97980766,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"2024","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998999834060669,"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":0.9998999834060669,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9909999966621399,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9871000051498413,"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":0.786728024482727},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5581037998199463},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5484382510185242},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5346891283988953},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.5079041123390198},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45461899042129517},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.44337916374206543},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.43708986043930054},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4175131320953369},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.20751458406448364}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.786728024482727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5581037998199463},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5484382510185242},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5346891283988953},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.5079041123390198},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45461899042129517},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.44337916374206543},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.43708986043930054},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4175131320953369},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.20751458406448364},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/isbi56570.2024.10635578","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi56570.2024.10635578","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},{"id":"pmid:39371472","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39371472","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":"Proceedings. IEEE International Symposium on Biomedical Imaging","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11450559","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11450559","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11450559/pdf/nihms-1972093.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc IEEE Int Symp Biomed Imaging","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:11450559","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11450559","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11450559/pdf/nihms-1972093.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc IEEE Int Symp Biomed Imaging","raw_type":"Text"},"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G113497091","display_name":null,"funder_award_id":"P30GM145646","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337354","display_name":"National Institute of General Medical Sciences","ror":"https://ror.org/04q48ey07"},{"id":"https://openalex.org/F4320338440","display_name":"HORIZON EUROPE Health","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4401753183.pdf","grobid_xml":"https://content.openalex.org/works/W4401753183.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2580611662","https://openalex.org/W2776937175","https://openalex.org/W2972101069","https://openalex.org/W2984544647","https://openalex.org/W3090745149","https://openalex.org/W3094502228","https://openalex.org/W3138115293","https://openalex.org/W3138516171","https://openalex.org/W3184815793","https://openalex.org/W3202236840","https://openalex.org/W4223929214","https://openalex.org/W4286437542","https://openalex.org/W4312845113","https://openalex.org/W4322494574","https://openalex.org/W4376631151","https://openalex.org/W6631190155","https://openalex.org/W6784333009","https://openalex.org/W6810330620"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W1514924336","https://openalex.org/W3183901164","https://openalex.org/W2951211570","https://openalex.org/W3176438653","https://openalex.org/W3135818718","https://openalex.org/W4290188444","https://openalex.org/W3003905048","https://openalex.org/W2253429366","https://openalex.org/W3127975138"],"abstract_inverted_index":{"Traditional":[0],"deep":[1],"learning":[2],"approaches":[3],"for":[4],"breast":[5],"cancer":[6],"classification":[7],"has":[8],"predominantly":[9],"concentrated":[10],"on":[11,83],"single-view":[12],"analysis.":[13],"In":[14,72],"clinical":[15],"practice,":[16],"however,":[17],"radiologists":[18],"concurrently":[19],"examine":[20],"all":[21],"views":[22,33,118],"within":[23],"a":[24,66,95,128],"mammography":[25],"exam,":[26],"leveraging":[27],"the":[28,39,103,111,120,133,144],"inherent":[29],"correlations":[30],"in":[31,88],"these":[32],"to":[34,65,85],"effectively":[35],"detect":[36],"tumors.":[37],"Acknowledging":[38],"significance":[40],"of":[41,68,106,114,132,137],"multi-view":[42,79,107],"analysis,":[43],"some":[44],"studies":[45],"have":[46],"introduced":[47],"methods":[48],"that":[49],"independently":[50],"process":[51],"mammogram":[52],"views,":[53],"either":[54],"through":[55],"distinct":[56],"convolutional":[57],"branches":[58],"or":[59],"simple":[60],"fusion":[61],"strategies,":[62],"inadvertently":[63],"leading":[64],"loss":[67],"crucial":[69],"inter-view":[70],"correlations.":[71],"this":[73,115],"paper,":[74],"we":[75,126],"propose":[76],"an":[77],"innovative":[78],"network":[80],"exclusively":[81],"based":[82],"transformers":[84],"address":[86],"challenges":[87],"mammographic":[89],"image":[90],"classification.":[91],"Our":[92,150],"approach":[93],"introduces":[94],"novel":[96],"shifted":[97],"window-based":[98],"dynamic":[99],"attention":[100],"block,":[101],"facilitating":[102],"effective":[104],"integration":[105],"information":[108,116],"and":[109,135,146],"promoting":[110],"coherent":[112],"transfer":[113],"between":[117],"at":[119,155],"spatial":[121],"feature":[122],"map":[123],"level.":[124],"Furthermore,":[125],"conduct":[127],"comprehensive":[129],"comparative":[130],"analysis":[131],"performance":[134],"effectiveness":[136],"transformer-based":[138],"models":[139],"under":[140],"diverse":[141],"settings,":[142],"employing":[143],"CBIS-DDSM":[145],"Vin-Dr":[147],"Mammo":[148],"datasets.":[149],"code":[151],"is":[152],"publicly":[153],"available":[154],"https://github.com/prithuls/MV-Swin-T.":[156]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-14T08:36:36.166977","created_date":"2025-10-10T00:00:00"}
