{"id":"https://openalex.org/W4406260983","doi":"https://doi.org/10.1109/bibm62325.2024.10821967","title":"Edge-Enhanced Dilated Residual Attention Network for Multimodal Medical Image Fusion","display_name":"Edge-Enhanced Dilated Residual Attention Network for Multimodal Medical Image Fusion","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406260983","doi":"https://doi.org/10.1109/bibm62325.2024.10821967"},"language":"en","primary_location":{"id":"doi:10.1109/bibm62325.2024.10821967","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10821967","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5104687891","display_name":"Zhou Meng","orcid":"https://orcid.org/0009-0009-9781-883X"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Meng Zhou","raw_affiliation_strings":["University of Toronto,Department of Computer Science,Toronto,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Toronto,Department of Computer Science,Toronto,Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049930699","display_name":"Yuxuan Zhang","orcid":"https://orcid.org/0000-0001-6141-6825"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yuxuan Zhang","raw_affiliation_strings":["University of Toronto,Department of Computer Science,Toronto,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Toronto,Department of Computer Science,Toronto,Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101626367","display_name":"Xiaolan Xu","orcid":"https://orcid.org/0000-0002-7120-177X"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xiaolan Xu","raw_affiliation_strings":["University of Toronto,Department of Computer Science,Toronto,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Toronto,Department of Computer Science,Toronto,Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiayi Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jiayi Wang","raw_affiliation_strings":["McGill University,Desautels Faculty of Management,Montreal,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGill University,Desautels Faculty of Management,Montreal,Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034208717","display_name":"Farzad Khalvati","orcid":"https://orcid.org/0000-0001-5616-8660"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Farzad Khalvati","raw_affiliation_strings":["University of Toronto,Department of Computer Science,Toronto,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Toronto,Department of Computer Science,Toronto,Canada","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4108","last_page":"4111"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9993000030517578,"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":0.9993000030517578,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9478999972343445,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9164999723434448,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6934356689453125},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5968896150588989},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5724868178367615},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5586792230606079},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5430407524108887},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.49541032314300537},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3824094533920288},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1430673599243164}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6934356689453125},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5968896150588989},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5724868178367615},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5586792230606079},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5430407524108887},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.49541032314300537},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3824094533920288},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1430673599243164}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm62325.2024.10821967","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10821967","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1641498739","https://openalex.org/W2950308928","https://openalex.org/W2950689937","https://openalex.org/W2963495494","https://openalex.org/W2963787388","https://openalex.org/W2966009696","https://openalex.org/W3035557850","https://openalex.org/W3132646223","https://openalex.org/W3212907520","https://openalex.org/W4283732315","https://openalex.org/W4285278336","https://openalex.org/W4386902810","https://openalex.org/W4389429244","https://openalex.org/W6696085341","https://openalex.org/W6751733626","https://openalex.org/W6846871407"],"related_works":["https://openalex.org/W2560215812","https://openalex.org/W2949601986","https://openalex.org/W2788972299","https://openalex.org/W2521347458","https://openalex.org/W2373946551","https://openalex.org/W2032636564","https://openalex.org/W2350275110","https://openalex.org/W3035059915","https://openalex.org/W2381578981","https://openalex.org/W3034835492"],"abstract_inverted_index":{"Multimodal":[0],"medical":[1],"image":[2],"fusion":[3,41,77,139,172],"is":[4],"a":[5,17,98,108,121,137,176],"crucial":[6],"task":[7],"that":[8,102,161],"combines":[9],"complementary":[10],"information":[11],"from":[12],"different":[13],"imaging":[14],"modalities":[15],"into":[16],"unified":[18],"representation,":[19],"thereby":[20],"enhancing":[21],"diagnostic":[22],"accuracy":[23],"and":[24,36,55,76,132,171],"treatment":[25],"planning.":[26],"While":[27],"deep":[28],"learning":[29],"methods,":[30],"particularly":[31],"Convolutional":[32],"Neural":[33],"Networks":[34],"(CNNs)":[35],"Transformers,":[37],"have":[38],"significantly":[39],"advanced":[40],"performance,":[42],"some":[43],"of":[44,90,146],"the":[45,66,74,87,143],"existing":[46],"CNN-based":[47,100],"methods":[48,167],"fall":[49],"short":[50],"in":[51,72,168],"capturing":[52],"fine-grained":[53],"multiscale":[54,116],"edge":[56,126],"features,":[57],"leading":[58],"to":[59,124],"suboptimal":[60],"feature":[61,117],"integration.":[62],"Transformer-based":[63],"models,":[64],"on":[65,142],"other":[67],"hand,":[68],"are":[69],"computationally":[70],"intensive":[71],"both":[73],"training":[75,155],"stages,":[78],"making":[79,174],"them":[80],"impractical":[81],"for":[82,114,180],"real-time":[83],"clinical":[84,88,182],"use.":[85],"Moreover,":[86],"application":[89],"fused":[91],"images":[92],"remains":[93],"unexplored.":[94],"This":[95],"work":[96],"proposes":[97],"novel":[99],"architecture":[101],"addresses":[103],"these":[104],"limitations":[105],"by":[106],"introducing":[107],"Dilated":[109],"Residual":[110],"Attention":[111],"Network":[112],"Module":[113],"effective":[115],"extraction,":[118],"coupled":[119],"with":[120],"gradient":[122],"operator":[123],"enhance":[125],"detail":[127],"learning.":[128],"To":[129],"ensure":[130],"fast":[131],"efficient":[133],"fusion,":[134],"we":[135],"present":[136],"parameter-free":[138],"strategy":[140],"based":[141],"nuclear":[144],"norm":[145],"softmax":[147],"weights,":[148],"which":[149],"requires":[150],"no":[151],"additional":[152],"computations":[153],"during":[154],"or":[156],"inference.":[157],"Extensive":[158],"experiments":[159],"demonstrate":[160],"our":[162],"approach":[163],"outperforms":[164],"various":[165],"baseline":[166],"visual":[169],"quality":[170],"speed,":[173],"it":[175],"possible":[177],"practical":[178],"solution":[179],"real-world":[181],"applications.":[183],"Code":[184],"will":[185],"be":[186],"released":[187],"at":[188],"https://github.com/simonZhou86/endran.":[189]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":6}],"updated_date":"2026-07-21T08:15:58.654021","created_date":"2025-10-10T00:00:00"}
