{"id":"https://openalex.org/W4412605353","doi":"https://doi.org/10.1109/tmm.2025.3590930","title":"Multi-Grained Vision-and-Language Model for Medical Image and Text Alignment","display_name":"Multi-Grained Vision-and-Language Model for Medical Image and Text Alignment","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412605353","doi":"https://doi.org/10.1109/tmm.2025.3590930"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2025.3590930","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3590930","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100652907","display_name":"Huimin Yan","orcid":"https://orcid.org/0009-0000-8342-7605"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huimin Yan","raw_affiliation_strings":["Institute of Intelligent Information Processing, Shanxi University, Taiyuan, China"],"raw_orcid":"https://orcid.org/0009-0000-8342-7605","affiliations":[{"raw_affiliation_string":"Institute of Intelligent Information Processing, Shanxi University, Taiyuan, China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018266083","display_name":"Xian Yang","orcid":"https://orcid.org/0000-0002-1496-8923"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Xian Yang","raw_affiliation_strings":["Alliance Manchester Business School, The University of Manchester, Manchester, U.K"],"raw_orcid":"https://orcid.org/0000-0002-1496-8923","affiliations":[{"raw_affiliation_string":"Alliance Manchester Business School, The University of Manchester, Manchester, U.K","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046818326","display_name":"Liang Bai","orcid":"https://orcid.org/0000-0002-0380-2995"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Bai","raw_affiliation_strings":["Institute of Intelligent Information Processing, Shanxi University, Taiyuan, China"],"raw_orcid":"https://orcid.org/0000-0002-0380-2995","affiliations":[{"raw_affiliation_string":"Institute of Intelligent Information Processing, Shanxi University, Taiyuan, China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiamin Li","orcid":"https://orcid.org/0009-0008-1663-9438"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiamin Li","raw_affiliation_strings":["Institute of Intelligent Information Processing, Shanxi University, Taiyuan, China"],"raw_orcid":"https://orcid.org/0009-0008-1663-9438","affiliations":[{"raw_affiliation_string":"Institute of Intelligent Information Processing, Shanxi University, Taiyuan, China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106626932","display_name":"Jiye Liang","orcid":"https://orcid.org/0000-0001-5887-9327"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiye Liang","raw_affiliation_strings":["Institute of Intelligent Information Processing, Shanxi University, Taiyuan, China"],"raw_orcid":"https://orcid.org/0000-0001-5887-9327","affiliations":[{"raw_affiliation_string":"Institute of Intelligent Information Processing, Shanxi University, Taiyuan, China","institution_ids":["https://openalex.org/I181877577"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7655,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.72538503,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"27","issue":null,"first_page":"6780","last_page":"6792"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9842000007629395,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9842000007629395,"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":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8659999370574951},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5793376564979553},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5655745267868042},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.47029468417167664},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.46613380312919617},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.33623677492141724}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8659999370574951},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5793376564979553},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5655745267868042},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.47029468417167664},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46613380312919617},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.33623677492141724}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tmm.2025.3590930","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3590930","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:publications/a0e0d405-095b-460c-ad71-ee4444b1c975","is_oa":false,"landing_page_url":"https://research.manchester.ac.uk/en/publications/a0e0d405-095b-460c-ad71-ee4444b1c975","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Yan, H, Yang, X, Bai, L, Li, J & Liang, J 2025, 'Multi-Grained Vision-and-Language Model for Medical Image and Text Alignment', IEEE Transactions on Multimedia. https://doi.org/10.1109/TMM.2025.3590930","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2176691914","display_name":null,"funder_award_id":"62432006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5929282161","display_name":null,"funder_award_id":"2021ZD0113303","funder_id":"https://openalex.org/F4320329860","funder_display_name":"National Science and Technology Major Project"},{"id":"https://openalex.org/G6929609165","display_name":null,"funder_award_id":"62276159","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1933349210","https://openalex.org/W2194775991","https://openalex.org/W2896457183","https://openalex.org/W2914203365","https://openalex.org/W2920885526","https://openalex.org/W2962858109","https://openalex.org/W2963466845","https://openalex.org/W2963716420","https://openalex.org/W2995225687","https://openalex.org/W3034837210","https://openalex.org/W3035524453","https://openalex.org/W3090449556","https://openalex.org/W3091588028","https://openalex.org/W3135057764","https://openalex.org/W3138516171","https://openalex.org/W3173909648","https://openalex.org/W3201906559","https://openalex.org/W4281643269","https://openalex.org/W4285215683","https://openalex.org/W4312533035","https://openalex.org/W4312784228","https://openalex.org/W4313156423","https://openalex.org/W4313855701","https://openalex.org/W4375928908","https://openalex.org/W4378697123","https://openalex.org/W4385573131","https://openalex.org/W4387789891","https://openalex.org/W4389252439","https://openalex.org/W4389317792","https://openalex.org/W4390872699","https://openalex.org/W4391216079","https://openalex.org/W4392152051","https://openalex.org/W4392903030","https://openalex.org/W4396909863","https://openalex.org/W4399146252","https://openalex.org/W4399666152","https://openalex.org/W4401751272","https://openalex.org/W4403650347"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"The":[0],"increasing":[1],"interest":[2],"in":[3,124],"learning":[4,84],"from":[5,90],"paired":[6],"medical":[7,61,87],"images":[8,62,114],"and":[9,63,71,85,115,130,147,166,176,190,209],"textual":[10,91],"reports":[11,92],"highlights":[12],"the":[13,37,40,49,80,98,102,118,153,182,188,195,206],"need":[14],"for":[15,109],"methods":[16],"that":[17],"can":[18,35],"achieve":[19,170],"multi-grained":[20,58],"alignment":[21,99,173],"between":[22,60,145,174,187],"these":[23],"two":[24],"modalities.":[25,192],"However,":[26],"most":[27],"existing":[28],"approaches":[29],"overlook":[30],"finegrained":[31,171],"semantic":[32,172],"alignment,":[33,76,161],"which":[34,55],"constrain":[36],"quality":[38,154],"of":[39,82,155,185,197],"generated":[41],"representations.":[42,158],"To":[43,193],"tackle":[44],"this":[45],"problem,":[46],"we":[47,105,162,201],"propose":[48,106],"Multi-Grained":[50],"Vision-and-Language":[51],"Alignment":[52],"(MGVLA)":[53],"model,":[54,200],"effectively":[56,180],"leverages":[57],"correspondences":[59],"texts":[64,116],"at":[65],"different":[66,183],"levels,":[67],"including":[68],"disease,":[69],"instance,":[70],"token":[72],"levels.":[73],"For":[74,159],"disease-level":[75],"our":[77,140,156,198],"approach":[78,141,179],"adopts":[79],"concept":[81],"contrastive":[83],"uses":[86],"terminologies":[88],"detected":[89],"as":[93,127,134],"soft":[94],"labels":[95],"to":[96,142,169],"guide":[97],"process.":[100],"At":[101],"instance":[103],"level,":[104],"a":[107,164],"strategy":[108,138],"sampling":[110],"hard":[111,135],"negatives,":[112],"where":[113],"with":[117],"same":[119],"disease":[120,128],"type":[121],"but":[122],"differing":[123],"details":[125],"such":[126],"locations":[129],"severity":[131],"are":[132],"considered":[133],"negatives.":[136],"This":[137,178],"helps":[139],"better":[143],"distinguish":[144],"positive":[146],"negative":[148],"image-text":[149,207],"pairs,":[150],"ultimately":[151],"enhancing":[152],"learned":[157],"token-level":[160],"employ":[163],"masking":[165],"recovery":[167],"technique":[168],"patches":[175],"sub-words.":[177],"aligns":[181],"levels":[184],"granularity":[186],"image":[189],"language":[191],"assess":[194],"efficacy":[196],"MGVLA":[199],"conduct":[202],"comprehensive":[203],"experiments":[204],"on":[205],"retrieval":[208],"phrase":[210],"grounding":[211],"tasks.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
