{"id":"https://openalex.org/W4415626576","doi":"https://doi.org/10.1109/tcsvt.2025.3626562","title":"FAMAFuse: Functional-Anatomical Multiscale Attention for Multimodal Image Fusion","display_name":"FAMAFuse: Functional-Anatomical Multiscale Attention for Multimodal Image Fusion","publication_year":2025,"publication_date":"2025-10-28","ids":{"openalex":"https://openalex.org/W4415626576","doi":"https://doi.org/10.1109/tcsvt.2025.3626562"},"language":null,"primary_location":{"id":"doi:10.1109/tcsvt.2025.3626562","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2025.3626562","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","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/A5113374630","display_name":"Alpha Alimamy Kamara","orcid":"https://orcid.org/0009-0008-9252-5950"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Alpha Alimamy Kamara","raw_affiliation_strings":["School of Computer Science and Engineering, Central South University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046019676","display_name":"Shiwen He","orcid":"https://orcid.org/0000-0003-0549-4970"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiwen He","raw_affiliation_strings":["School of Computer Science and Engineering, Central South University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070245509","display_name":"Abdul Joseph Fofanah","orcid":"https://orcid.org/0000-0001-8742-9325"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]},{"id":"https://openalex.org/I160993911","display_name":"Queensland University of Technology","ror":"https://ror.org/03pnv4752","country_code":"AU","type":"education","lineage":["https://openalex.org/I160993911"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Abdul Joseph Fofanah","raw_affiliation_strings":["School of Information and Communication Technology, Griffith University, Brisbane, QLD, Australia","School of Information and Communication Technology, Griffith University, 170 Kessels Road, Brisbane, Queensland, Australia"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Technology, Griffith University, Brisbane, QLD, Australia","institution_ids":["https://openalex.org/I11701301"]},{"raw_affiliation_string":"School of Information and Communication Technology, Griffith University, 170 Kessels Road, Brisbane, Queensland, Australia","institution_ids":["https://openalex.org/I11701301","https://openalex.org/I160993911"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5113374630"],"corresponding_institution_ids":["https://openalex.org/I139660479"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.45943723,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":"3","first_page":"3215","last_page":"3230"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.19050000607967377,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.19050000607967377,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.14990000426769257,"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":0.09239999949932098,"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/image-fusion","display_name":"Image fusion","score":0.6812000274658203},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5845000147819519},{"id":"https://openalex.org/keywords/medical-diagnosis","display_name":"Medical diagnosis","score":0.5479999780654907},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5415999889373779},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48919999599456787},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.43790000677108765},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.43459999561309814},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4198000133037567},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4050000011920929},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.364300012588501}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7925999760627747},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7214999794960022},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.6812000274658203},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5845000147819519},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.5479999780654907},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5415999889373779},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48919999599456787},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4577000141143799},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.43790000677108765},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.43459999561309814},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4198000133037567},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4050000011920929},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.364300012588501},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.36090001463890076},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.358599990606308},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.34209999442100525},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.32260000705718994},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.31139999628067017},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.3059999942779541},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2946000099182129},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.29190000891685486},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.287200003862381},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.2865999937057495},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.2847999930381775},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.2533999979496002},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.25049999356269836},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.25}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2025.3626562","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2025.3626562","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W1580436348","https://openalex.org/W1964641132","https://openalex.org/W1997596006","https://openalex.org/W2009758395","https://openalex.org/W2054273865","https://openalex.org/W2133665775","https://openalex.org/W2153777140","https://openalex.org/W2552737937","https://openalex.org/W2798741430","https://openalex.org/W2895328943","https://openalex.org/W2912581987","https://openalex.org/W2966253851","https://openalex.org/W2991617172","https://openalex.org/W2997591000","https://openalex.org/W2997694174","https://openalex.org/W2999333317","https://openalex.org/W3000491333","https://openalex.org/W3007473102","https://openalex.org/W3020707676","https://openalex.org/W3031508018","https://openalex.org/W3036170900","https://openalex.org/W3042233471","https://openalex.org/W3043904761","https://openalex.org/W3046464322","https://openalex.org/W3082944873","https://openalex.org/W3085582435","https://openalex.org/W3119514771","https://openalex.org/W3121121992","https://openalex.org/W3133676655","https://openalex.org/W3138516171","https://openalex.org/W3159235206","https://openalex.org/W3190808861","https://openalex.org/W4225829036","https://openalex.org/W4283732315","https://openalex.org/W4285158820","https://openalex.org/W4286361941","https://openalex.org/W4288391270","https://openalex.org/W4308234335","https://openalex.org/W4313555022","https://openalex.org/W4321488347","https://openalex.org/W4362562924","https://openalex.org/W4366482244","https://openalex.org/W4375928908","https://openalex.org/W4376131895","https://openalex.org/W4377007227","https://openalex.org/W4379116886","https://openalex.org/W4382119107","https://openalex.org/W4384916907","https://openalex.org/W4386902810","https://openalex.org/W4386986828","https://openalex.org/W4387682254","https://openalex.org/W4387872544","https://openalex.org/W4388003997","https://openalex.org/W4390872797","https://openalex.org/W4392969647","https://openalex.org/W4394966893","https://openalex.org/W4398152662","https://openalex.org/W4401200174","https://openalex.org/W4401247055","https://openalex.org/W4402753825","https://openalex.org/W4405303762","https://openalex.org/W4405303798","https://openalex.org/W4406260983","https://openalex.org/W4406891929","https://openalex.org/W4408323597","https://openalex.org/W4412404110"],"related_works":[],"abstract_inverted_index":{"Functional":[0],"and":[1,23,42,67,115,147,173,205,209],"anatomical":[2,24,68,96],"image":[3,69],"fusion":[4,93,104,135,157,171],"plays":[5],"an":[6],"important":[7],"role":[8],"in":[9,170,177],"medical":[10,207],"applications":[11],"by":[12,166],"combining":[13],"information":[14],"from":[15],"multiple":[16,49],"imaging":[17,139],"modalities":[18],"to":[19,38,76,130,168,175],"retain":[20],"functional":[21,66],"features":[22,47,97],"details.":[25],"Although":[26],"deep":[27],"learning-based":[28],"methods":[29,35],"have":[30],"advanced":[31],"the":[32,81,92,101,119],"field,":[33],"existing":[34,164],"often":[36],"struggle":[37],"capture":[39],"local":[40,113],"details":[41,114],"global":[43,89],"context,":[44,90],"especially":[45],"when":[46],"span":[48],"scales.":[50],"To":[51],"address":[52],"these":[53,78],"limitations,":[54],"we":[55],"propose":[56],"FAMAFuse,":[57],"a":[58,126,190,199],"novel":[59],"multiscale":[60,120,132],"attention":[61,83],"mechanism":[62],"designed":[63],"specifically":[64],"for":[65,193,202],"fusion.":[70],"FAMAFuse":[71,143,162,181],"integrates":[72],"three":[73],"key":[74],"innovations":[75],"overcome":[77],"challenges.":[79],"First,":[80],"spatial":[82],"residual":[84],"module":[85,106,123],"(SARM)":[86],"models":[87],"long-range":[88],"ensuring":[91],"of":[94],"relevant":[95],"across":[98,137,185],"modalities.":[99,140],"Second,":[100],"inter-modal":[102],"feature":[103],"(IMFF)":[105],"fuses":[107],"multi-source":[108],"features,":[109,133],"enhancing":[110],"interaction":[111],"between":[112],"broader":[116],"structures.":[117],"Finally,":[118],"gaussian":[121,128],"attention-infused":[122],"(M-GAIM)":[124],"leverages":[125],"learnable":[127],"kernel":[129],"extract":[131],"improving":[134],"quality":[136,172],"various":[138],"We":[141],"validated":[142],"on":[144],"SPECT-MRI,":[145],"PET-MRI,":[146],"CT-MRI":[148],"datasets.":[149],"Experimental":[150],"results":[151],"demonstrate":[152],"significant":[153],"improvements":[154],"over":[155],"state-of-the-art":[156],"methods.":[158],"In":[159],"quantitative":[160],"evaluations,":[161],"outperforms":[163],"techniques":[165],"4%":[167],"10%":[169],"0.5%":[174],"6%":[176],"structural":[178],"preservation.":[179],"Furthermore,":[180],"exhibits":[182],"excellent":[183],"generalisation":[184],"different":[186],"modalities,":[187],"making":[188],"it":[189],"suitable":[191],"tool":[192],"clinical":[194,210],"imaging.":[195],"This":[196],"method":[197],"represents":[198],"promising":[200],"solution":[201],"more":[203],"accurate":[204],"informative":[206],"diagnoses":[208],"research.":[211],"The":[212],"source":[213],"code":[214],"is":[215],"available":[216],"at:":[217],"https://github.com/Alphaalimamy/famafuse.":[218]},"counts_by_year":[],"updated_date":"2026-03-09T07:00:12.390032","created_date":"2025-10-29T00:00:00"}
