{"id":"https://openalex.org/W7126070679","doi":"https://doi.org/10.1109/bibm66473.2025.11356218","title":"Modality-Guided Edge Fusion and Semantic Enhancement for Multi-Modal Brain Tumor Segmentation","display_name":"Modality-Guided Edge Fusion and Semantic Enhancement for Multi-Modal Brain Tumor Segmentation","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126070679","doi":"https://doi.org/10.1109/bibm66473.2025.11356218"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356218","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-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/A5036955242","display_name":"Weixun Zhou","orcid":"https://orcid.org/0000-0002-3270-7268"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Wentong Zhou","raw_affiliation_strings":["Graduate School of Biomedical Engineering, Tohoku University,Sendai,Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Biomedical Engineering, Tohoku University,Sendai,Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102977933","display_name":"Yuwen Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuwen Zeng","raw_affiliation_strings":["Advanced Institute of Convergence Knowledge Informatics, Tohoku University,Sendai,Japan"],"affiliations":[{"raw_affiliation_string":"Advanced Institute of Convergence Knowledge Informatics, Tohoku University,Sendai,Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124243174","display_name":"Xiaoyong Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210087517","display_name":"Sendai National College of Technology","ror":"https://ror.org/00293y771","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210087517"]},{"id":"https://openalex.org/I4210120810","display_name":"National Institute of Technology","ror":"https://ror.org/02xqkcw08","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210120810"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xiaoyong Zhang","raw_affiliation_strings":["National Institute of Technology, Sendai College,Sendai,Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Technology, Sendai College,Sendai,Japan","institution_ids":["https://openalex.org/I4210087517","https://openalex.org/I4210120810"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019250315","display_name":"R. Li","orcid":"https://orcid.org/0009-0003-5593-4476"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ruili Li","raw_affiliation_strings":["Tohoku University Graduate School of Medicine,Sendai,Japan"],"affiliations":[{"raw_affiliation_string":"Tohoku University Graduate School of Medicine,Sendai,Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013100193","display_name":"Arata Nagai","orcid":"https://orcid.org/0009-0005-4865-4235"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Arata Nagai","raw_affiliation_strings":["Tohoku University Graduate School of Medicine,Sendai,Japan"],"affiliations":[{"raw_affiliation_string":"Tohoku University Graduate School of Medicine,Sendai,Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057784364","display_name":"Masayuki Kanamori","orcid":"https://orcid.org/0000-0002-3380-1192"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masayuki Kanamori","raw_affiliation_strings":["Tohoku University Graduate School of Medicine,Sendai,Japan"],"affiliations":[{"raw_affiliation_string":"Tohoku University Graduate School of Medicine,Sendai,Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064749082","display_name":"Hidenori Endo","orcid":"https://orcid.org/0000-0003-1472-6032"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hidenori Endo","raw_affiliation_strings":["Tohoku University Graduate School of Medicine,Sendai,Japan"],"affiliations":[{"raw_affiliation_string":"Tohoku University Graduate School of Medicine,Sendai,Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074615107","display_name":"Kuniyasu Niizuma","orcid":"https://orcid.org/0000-0001-9282-6499"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kuniyasu Niizuma","raw_affiliation_strings":["Tohoku University Graduate School of Medicine,Sendai,Japan"],"affiliations":[{"raw_affiliation_string":"Tohoku University Graduate School of Medicine,Sendai,Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026817114","display_name":"N. Homma","orcid":null},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Noriyasu Homma","raw_affiliation_strings":["Tohoku University Graduate School of Medicine,Sendai,Japan"],"affiliations":[{"raw_affiliation_string":"Tohoku University Graduate School of Medicine,Sendai,Japan","institution_ids":["https://openalex.org/I201537933"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5036955242"],"corresponding_institution_ids":["https://openalex.org/I201537933"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.72373953,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6668","last_page":"6675"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.8651999831199646,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.8651999831199646,"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":0.0722000002861023,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.013100000098347664,"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/segmentation","display_name":"Segmentation","score":0.6424999833106995},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.541700005531311},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4749000072479248},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4745999872684479},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47110000252723694},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.43290001153945923},{"id":"https://openalex.org/keywords/brain-tumor","display_name":"Brain tumor","score":0.3750999867916107},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.3734000027179718}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7111999988555908},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6992999911308289},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6424999833106995},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.541700005531311},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4749000072479248},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4745999872684479},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47110000252723694},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.43290001153945923},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37720000743865967},{"id":"https://openalex.org/C2779130545","wikidata":"https://www.wikidata.org/wiki/Q233309","display_name":"Brain tumor","level":2,"score":0.3750999867916107},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3734000027179718},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.37310001254081726},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.3675000071525574},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.35839998722076416},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.35499998927116394},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.3260999917984009},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3025999963283539},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.296999990940094},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.2551000118255615},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356218","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5981824398040771,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1641498739","https://openalex.org/W1901129140","https://openalex.org/W2464708700","https://openalex.org/W2751069891","https://openalex.org/W2884585870","https://openalex.org/W3013630101","https://openalex.org/W3094502228","https://openalex.org/W3123264927","https://openalex.org/W3203841574","https://openalex.org/W3204426737","https://openalex.org/W4212875960","https://openalex.org/W4221163766","https://openalex.org/W4295938041","https://openalex.org/W4296640326","https://openalex.org/W4307726656","https://openalex.org/W4308310215","https://openalex.org/W4308923888","https://openalex.org/W4311767714","https://openalex.org/W4391469551","https://openalex.org/W4393147960","https://openalex.org/W4396930028","https://openalex.org/W4402259364","https://openalex.org/W4406259768","https://openalex.org/W4406260509","https://openalex.org/W4408353639"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"brain":[1,48],"tumor":[2,12,24,49,60],"segmentation":[3,50,143],"is":[4],"essential":[5],"for":[6,36,46],"clinical":[7],"tasks":[8],"such":[9],"as":[10,90],"diagnosis,":[11],"localization,":[13],"and":[14,58,78,98,105,126,145],"surgical":[15],"planning.":[16],"Although":[17],"multi-modality":[18],"MRI":[19],"provides":[20],"complementary":[21],"information":[22],"about":[23],"subregions,":[25],"the":[26,117,137,149,154,181],"difference":[27],"of":[28,156,183],"image":[29],"characteristics":[30],"across":[31],"modalities":[32,111],"poses":[33],"significant":[34],"challenges":[35],"effective":[37],"integration.":[38],"To":[39],"address":[40],"this,":[41],"we":[42],"proposed":[43],"a":[44,79,165],"framework":[45],"multi-modal":[47],"that":[51,162,173],"enhances":[52],"boundary":[53],"consistency":[54],"through":[55],"modality-guided":[56],"fusion":[57,93,186],"strengthens":[59],"discrimination":[61],"via":[62],"semantic":[63,132],"attention":[64,128],"enhancement.":[65],"Our":[66],"method":[67],"incorporates":[68],"two":[69],"key":[70,166],"modules:":[71],"an":[72,91],"Edge-Enhanced":[73],"MultiModal":[74],"Fusion":[75],"(EMF)":[76],"module":[77],"Residual":[80],"Convolutional":[81],"Block":[82],"Attention":[83],"Module":[84],"(ResCBAM).":[85],"The":[86],"EMF":[87,163],"module,":[88],"designed":[89],"early":[92],"component,":[94],"leverages":[95],"3D":[96],"Sobel":[97],"Laplacian":[99],"filters":[100],"to":[101,112,129],"extract":[102],"structural":[103],"features":[104],"selectively":[106],"integrates":[107],"T1c":[108],"with":[109,124],"other":[110],"improve":[113],"boundary-aware":[114],"representation.":[115],"At":[116],"network":[118],"bottleneck,":[119],"ResCBAM":[120],"combines":[121],"residual":[122],"connections":[123],"channel":[125],"spatial":[127],"enhance":[130],"high-level":[131],"features.":[133],"Extensive":[134],"experiments":[135],"on":[136,148],"BraTS2023":[138],"public":[139],"dataset":[140,152],"demonstrate":[141,161],"strong":[142],"performance,":[144],"further":[146],"evaluation":[147],"external":[150],"BraTS2025":[151],"confirms":[153],"robustness":[155],"our":[157],"approach.":[158],"Ablation":[159],"studies":[160],"plays":[164],"role":[167],"in":[168],"extracting":[169],"high-quality,":[170],"modality-aware":[171],"representations":[172],"can":[174],"be":[175],"effectively":[176],"refined":[177],"by":[178],"ResCBAM,":[179],"highlighting":[180],"effectiveness":[182],"this":[184],"cooperative":[185],"design.":[187]},"counts_by_year":[],"updated_date":"2026-02-01T03:34:12.195049","created_date":"2026-01-30T00:00:00"}