{"id":"https://openalex.org/W7161253636","doi":"https://doi.org/10.1016/j.bspc.2026.110529","title":"Explainable dynamic fusion of GCNN and CNN for precise brain tumor analysis from MRI scans","display_name":"Explainable dynamic fusion of GCNN and CNN for precise brain tumor analysis from MRI scans","publication_year":2026,"publication_date":"2026-05-15","ids":{"openalex":"https://openalex.org/W7161253636","doi":"https://doi.org/10.1016/j.bspc.2026.110529"},"language":"en","primary_location":{"id":"doi:10.1016/j.bspc.2026.110529","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.bspc.2026.110529","pdf_url":null,"source":{"id":"https://openalex.org/S8427965","display_name":"Biomedical Signal Processing and Control","issn_l":"1746-8094","issn":["1746-8094","1746-8108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Biomedical Signal Processing and Control","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.bspc.2026.110529","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026620176","display_name":"Rizoan Toufiq","orcid":null},"institutions":[{"id":"https://openalex.org/I17477748","display_name":"Rajshahi University of Engineering and Technology","ror":"https://ror.org/049ysg747","country_code":"BD","type":"education","lineage":["https://openalex.org/I17477748"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Rizoan Toufiq","raw_affiliation_strings":["Rajshahi University of Engineering and Technology, Bangladesh"],"raw_orcid":"https://orcid.org/0009-0001-8067-9468","affiliations":[{"raw_affiliation_string":"Rajshahi University of Engineering and Technology, Bangladesh","institution_ids":["https://openalex.org/I17477748"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089264816","display_name":"Biprodip Pal","orcid":"https://orcid.org/0000-0002-8234-9382"},"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"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Biprodip Pal","raw_affiliation_strings":["Griffith University - GC Campus, Gold Coast, Australia"],"raw_orcid":"https://orcid.org/0000-0002-8234-9382","affiliations":[{"raw_affiliation_string":"Griffith University - GC Campus, Gold Coast, Australia","institution_ids":["https://openalex.org/I11701301"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5089264816"],"corresponding_institution_ids":["https://openalex.org/I11701301"],"apc_list":{"value":2420,"currency":"USD","value_usd":2420},"apc_paid":{"value":2420,"currency":"USD","value_usd":2420},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.94313643,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":"123","issue":null,"first_page":"110529","last_page":"110529"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.6561999917030334,"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"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.6561999917030334,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.1509000062942505,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.015599999576807022,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7355999946594238},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7106000185012817},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5949000120162964},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5085999965667725},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4724999964237213},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.45969998836517334},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4334999918937683}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8458999991416931},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7355999946594238},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7106000185012817},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6908000111579895},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5949000120162964},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5085999965667725},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4724999964237213},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.45969998836517334},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4334999918937683},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4122999906539917},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40119999647140503},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.39730000495910645},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37959998846054077},{"id":"https://openalex.org/C2779130545","wikidata":"https://www.wikidata.org/wiki/Q233309","display_name":"Brain tumor","level":2,"score":0.3675000071525574},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.bspc.2026.110529","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.bspc.2026.110529","pdf_url":null,"source":{"id":"https://openalex.org/S8427965","display_name":"Biomedical Signal Processing and Control","issn_l":"1746-8094","issn":["1746-8094","1746-8108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Biomedical Signal Processing and Control","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.bspc.2026.110529","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.bspc.2026.110529","pdf_url":null,"source":{"id":"https://openalex.org/S8427965","display_name":"Biomedical Signal Processing and Control","issn_l":"1746-8094","issn":["1746-8094","1746-8108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Biomedical Signal Processing and Control","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2065775807","https://openalex.org/W2161495439","https://openalex.org/W2962858109","https://openalex.org/W3089472426","https://openalex.org/W3120491988","https://openalex.org/W3121092655","https://openalex.org/W3136070377","https://openalex.org/W3159670968","https://openalex.org/W4224932948","https://openalex.org/W4292832893","https://openalex.org/W4293340419","https://openalex.org/W4294190735","https://openalex.org/W4295137765","https://openalex.org/W4321016247","https://openalex.org/W4322492185","https://openalex.org/W4353029436","https://openalex.org/W4386619298","https://openalex.org/W4387093916","https://openalex.org/W4389114031","https://openalex.org/W4390339811","https://openalex.org/W4394858373","https://openalex.org/W4395693611","https://openalex.org/W4398780537","https://openalex.org/W4399785574","https://openalex.org/W4403096778","https://openalex.org/W4403453839","https://openalex.org/W4403714128","https://openalex.org/W4404233093","https://openalex.org/W4404552640"],"related_works":[],"abstract_inverted_index":{"Precise":[0],"analysis":[1,93],"is":[2],"critical":[3],"for":[4,32,211],"automated":[5],"medical":[6],"image":[7],"analysis,":[8],"especially":[9],"in":[10,81,135],"brain":[11,60,91,136,215,234],"tumor":[12,92,182,216,235],"classification,":[13],"as":[14],"high":[15],"precision":[16],"ensures":[17],"accurate":[18,214],"treatment":[19],"decisions.":[20],"Existing":[21],"literature":[22],"has":[23],"primarily":[24],"focused":[25],"on":[26,78,188,255],"using":[27,258],"Convolutional":[28,99,105],"Neural":[29,100,106],"Networks":[30],"(CNNs)":[31],"hierarchical":[33,249],"feature":[34],"extraction,":[35],"often":[36],"employing":[37],"static":[38],"fusion":[39,210],"strategies":[40],"when":[41],"combining":[42,205],"multiple":[43],"models.":[44],"However,":[45],"these":[46,68],"approaches":[47],"overlook":[48],"the":[49,96,111,152,155,161,165,171,202,227,230],"potential":[50,203],"of":[51,59,98,113,154,170,180,204],"capturing":[52],"relational":[53,133],"structures":[54,134],"and":[55,103,121,131,178,208,213,229,241,248,262],"interactions":[56],"among":[57],"regions":[58],"images":[61],"from":[62],"a":[63,87,145,220],"graph":[64],"representation":[65,167],"perspective.":[66],"Additionally,":[67],"techniques":[69],"fail":[70],"to":[71,90,163,175,232,244],"adapt":[72],"inference":[73],"by":[74],"considering":[75],"model":[76,162,187],"correlations":[77],"individual":[79],"decisions":[80],"complex":[82,181],"data":[83],"environments.":[84],"We":[85,184],"propose":[86,144],"novel":[88],"approach":[89,159],"that":[94,124,149,224],"leverages":[95],"strengths":[97,169],"Network":[101,107],"(CNN)":[102],"Graph":[104],"(GCNN).":[108],"To":[109,139],"address":[110],"limitations":[112],"large,":[114],"resource-intensive":[115],"models,":[116],"we":[117,143],"introduce":[118],"lightweight":[119,206,239],"CNN":[120,228,242],"GCNN":[122,231,240],"architectures":[123,207,243],"efficiently":[125],"capture":[126,245],"both":[127],"local":[128],"spatial":[129,246],"patterns":[130],"global":[132],"MRI":[137,191],"scans.":[138],"further":[140],"enhance":[141,233],"performance,":[142],"Dynamic":[146,221],"Model":[147,222],"Fusion":[148,223],"adaptively":[150,225],"combines":[151,226],"outputs":[153],"two":[156,172],"networks.":[157],"This":[158],"allows":[160],"leverage":[164],"complementary":[166],"learning":[168],"architectures,":[173],"leading":[174],"improved":[176],"generalization":[177],"handling":[179],"variations.":[183],"evaluate":[185],"our":[186],"publicly":[189],"available":[190],"datasets,":[192,257],"demonstrating":[193],"significant":[194],"improvements":[195],"over":[196],"state-of-the-art":[197],"methods.":[198,266],"Our":[199],"results":[200],"highlight":[201],"dynamic":[209],"reliable":[212],"classification.":[217],"\u2022":[218,237,252],"Proposed":[219,238],"analysis.":[236],"relationships":[247],"features":[250],".":[251],"Rigorous":[253],"evaluation":[254],"public":[256],"XAI":[259],"based":[260],"explanations":[261],"benchmarking":[263],"against":[264],"SotA":[265]},"counts_by_year":[],"updated_date":"2026-05-16T06:11:02.277879","created_date":"2026-05-16T00:00:00"}