{"id":"https://openalex.org/W4416251056","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227390","title":"SwinFusion-XL: Multi-Scale Fusion and Cross xLSTM for Enhanced Brain Tumor Segmentation","display_name":"SwinFusion-XL: Multi-Scale Fusion and Cross xLSTM for Enhanced Brain Tumor Segmentation","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251056","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227390"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227390","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227390","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5071976167","display_name":"Zhaohan Zhang","orcid":"https://orcid.org/0000-0002-1634-7661"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhaohan Zhang","raw_affiliation_strings":["Zhejiang University,School of Software Technology,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,School of Software Technology,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051438193","display_name":"Rui Bao","orcid":"https://orcid.org/0000-0002-6083-8716"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruizuan Bao","raw_affiliation_strings":["Zhejiang University,College of Computer Science and Technology,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Computer Science and Technology,Hangzhou,China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027932715","display_name":"Jingjun Gu","orcid":"https://orcid.org/0000-0001-5714-9189"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingjun Gu","raw_affiliation_strings":["Zhejiang University,College of Computer Science and Technology,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Computer Science and Technology,Hangzhou,China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000295734","display_name":"Yue Yu","orcid":"https://orcid.org/0000-0003-3529-585X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Yu","raw_affiliation_strings":["Zhejiang University,School of Software Technology,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,School of Software Technology,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052757755","display_name":"Jiajun Bu","orcid":"https://orcid.org/0000-0002-1097-2044"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajun Bu","raw_affiliation_strings":["Zhejiang University,College of Computer Science and Technology,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Computer Science and Technology,Hangzhou,China","institution_ids":["https://openalex.org/I168879160"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5071976167"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37391709,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.8220000267028809,"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":0.8220000267028809,"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":0.12470000237226486,"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":0.012199999764561653,"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":0.7993000149726868},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7014999985694885},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5800999999046326},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5403000116348267},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4803999960422516},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4075999855995178},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.3833000063896179},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.3499000072479248}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7993000149726868},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7603999972343445},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7134000062942505},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7014999985694885},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5800999999046326},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5403000116348267},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4803999960422516},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41339999437332153},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4075999855995178},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3833000063896179},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.3499000072479248},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34209999442100525},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3009999990463257},{"id":"https://openalex.org/C2779130545","wikidata":"https://www.wikidata.org/wiki/Q233309","display_name":"Brain tumor","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2849999964237213},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.2596000134944916},{"id":"https://openalex.org/C2991673738","wikidata":"https://www.wikidata.org/wiki/Q5062122","display_name":"Brain disease","level":3,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227390","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227390","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2026651590","https://openalex.org/W2146353910","https://openalex.org/W2464708700","https://openalex.org/W2766140847","https://openalex.org/W2889615630","https://openalex.org/W2894802018","https://openalex.org/W2912147220","https://openalex.org/W2996290406","https://openalex.org/W3132455321","https://openalex.org/W3204177259","https://openalex.org/W4212875960","https://openalex.org/W4221163766","https://openalex.org/W4306734032","https://openalex.org/W4322707229","https://openalex.org/W4383904219","https://openalex.org/W4384570137","https://openalex.org/W4386160491","https://openalex.org/W4387095239","https://openalex.org/W4388999524","https://openalex.org/W4390278034"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"segmentation":[1,21,66,153],"of":[2,16,97],"brain":[3,82,138],"tumors,":[4],"especially":[5],"gliomas,":[6],"is":[7,117],"essential":[8],"for":[9,80,93],"medical":[10],"diagnosis,":[11],"treatment":[12],"planning,":[13],"and":[14,25,77,103,123,128,136],"monitoring":[15],"disease":[17],"progression.":[18],"Traditional":[19],"manual":[20],"methods":[22],"are":[23],"time-consuming":[24],"prone":[26],"to":[27,47,52,107,119],"variability,":[28],"while":[29],"deep":[30],"learning-based":[31],"approaches,":[32],"such":[33],"as":[34],"convolutional":[35],"neural":[36],"networks":[37],"(CNNs),":[38],"have":[39],"significantly":[40],"improved":[41],"performance.":[42,154],"However,":[43],"CNNs":[44],"often":[45],"struggle":[46],"capture":[48,124],"global":[49,78],"context":[50],"due":[51],"their":[53],"limited":[54],"receptive":[55],"fields.":[56],"To":[57],"address":[58],"these":[59],"challenges,":[60],"we":[61],"propose":[62],"SwinFusion-XL,":[63],"a":[64,87,112],"novel":[65],"model":[67,120,144],"based":[68],"on":[69,133],"the":[70,94,134],"Swin":[71],"UNETR":[72],"architecture":[73],"that":[74,142],"integrates":[75],"local":[76],"features":[79],"enhanced":[81],"tumor":[83,139],"segmentation.":[84],"SwinFusion-XL":[85],"leverages":[86],"Superficial":[88],"Mamba":[89],"Fusion":[90],"Module":[91,115],"(SMFM)":[92],"effective":[95],"integration":[96],"multi-scale":[98],"features,":[99],"combining":[100],"both":[101],"channel":[102],"spatial":[104],"attention":[105],"mechanisms":[106],"enhance":[108],"feature":[109],"representations.":[110],"Additionally,":[111],"Cross":[113],"xLSTM":[114],"(CxLSTM)":[116],"introduced":[118],"cross-feature":[121],"dependencies":[122],"long-range":[125],"spatial,":[126],"channel,":[127],"volumetric":[129],"relationships.":[130],"Extensive":[131],"experiments":[132],"BraTS2020":[135],"BraTS2021":[137],"datasets":[140],"demonstrate":[141],"our":[143],"consistently":[145],"outperforms":[146],"state-of-the-art":[147],"methods,":[148],"achieving":[149],"significant":[150],"improvements":[151],"in":[152]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-14T00:00:00"}
