{"id":"https://openalex.org/W4322495747","doi":"https://doi.org/10.1007/s12559-023-10126-7","title":"Large-Kernel Attention for 3D Medical Image Segmentation","display_name":"Large-Kernel Attention for 3D Medical Image Segmentation","publication_year":2023,"publication_date":"2023-02-27","ids":{"openalex":"https://openalex.org/W4322495747","doi":"https://doi.org/10.1007/s12559-023-10126-7","pmid":"https://pubmed.ncbi.nlm.nih.gov/38974012"},"language":"en","primary_location":{"id":"doi:10.1007/s12559-023-10126-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12559-023-10126-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12559-023-10126-7.pdf","source":{"id":"https://openalex.org/S133078663","display_name":"Cognitive Computation","issn_l":"1866-9956","issn":["1866-9956","1866-9964"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cognitive Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s12559-023-10126-7.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100348684","display_name":"Hao Li","orcid":"https://orcid.org/0000-0003-2476-0664"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hao Li","raw_affiliation_strings":["Department of Bioengineering, Faculty of Engineering, Imperial College London, London, UK","National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Bioengineering, Faculty of Engineering, Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100680991","display_name":"Nan Yang","orcid":"https://orcid.org/0000-0002-4542-3336"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yang Nan","raw_affiliation_strings":["National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017326471","display_name":"Javier Del Ser","orcid":"https://orcid.org/0000-0002-1260-9775"},"institutions":[{"id":"https://openalex.org/I169108374","display_name":"University of the Basque Country","ror":"https://ror.org/000xsnr85","country_code":"ES","type":"education","lineage":["https://openalex.org/I169108374"]},{"id":"https://openalex.org/I4210124459","display_name":"Association of Electronic and Information Technologies","ror":"https://ror.org/02trgdk48","country_code":"ES","type":"other","lineage":["https://openalex.org/I4210124459"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Javier Del Ser","raw_affiliation_strings":["TECNALIA, Basque Research & Technology Alliance (BRTA), Derio, Spain","University of the Basque Country (UPV/EHU), Bilbao, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TECNALIA, Basque Research & Technology Alliance (BRTA), Derio, Spain","institution_ids":["https://openalex.org/I4210124459"]},{"raw_affiliation_string":"University of the Basque Country (UPV/EHU), Bilbao, Spain","institution_ids":["https://openalex.org/I169108374"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100436460","display_name":"Guang Yang","orcid":"https://orcid.org/0000-0001-7344-7733"},"institutions":[{"id":"https://openalex.org/I4210096640","display_name":"Royal Brompton Hospital","ror":"https://ror.org/00cv4n034","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I2800036501","https://openalex.org/I4210096640"]},{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Guang Yang","raw_affiliation_strings":["National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, UK","Royal Brompton Hospital, London, UK"],"raw_orcid":"https://orcid.org/0000-0001-7344-7733","affiliations":[{"raw_affiliation_string":"National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Royal Brompton Hospital, London, UK","institution_ids":["https://openalex.org/I4210096640"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100436460"],"corresponding_institution_ids":["https://openalex.org/I4210096640","https://openalex.org/I47508984"],"apc_list":{"value":2790,"currency":"USD","value_usd":2790},"apc_paid":{"value":2790,"currency":"USD","value_usd":2790},"fwci":4.5536,"has_fulltext":true,"cited_by_count":48,"citation_normalized_percentile":{"value":0.96237952,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"16","issue":"4","first_page":"2063","last_page":"2077"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9993000030517578,"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"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9986000061035156,"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/computer-science","display_name":"Computer science","score":0.7746113538742065},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7709811329841614},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7512657642364502},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.561100423336029},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5586823225021362},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.55075603723526},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.4756602644920349},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.43424317240715027},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.429359495639801},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.42685043811798096},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41415566205978394},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.147172212600708},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10293439030647278}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7746113538742065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7709811329841614},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7512657642364502},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.561100423336029},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5586823225021362},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.55075603723526},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4756602644920349},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.43424317240715027},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.429359495639801},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.42685043811798096},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41415566205978394},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.147172212600708},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10293439030647278},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1007/s12559-023-10126-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12559-023-10126-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12559-023-10126-7.pdf","source":{"id":"https://openalex.org/S133078663","display_name":"Cognitive Computation","issn_l":"1866-9956","issn":["1866-9956","1866-9964"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cognitive Computation","raw_type":"journal-article"},{"id":"pmid:38974012","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38974012","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cognitive computation","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11226511","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11226511","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11226511/pdf/12559_2023_Article_10126.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Cognit Comput","raw_type":"Text"},{"id":"pmh:oai:dsp.tecnalia.com:11556/4987","is_oa":true,"landing_page_url":"https://hdl.handle.net/11556/4987","pdf_url":null,"source":{"id":"https://openalex.org/S4306402037","display_name":"TECNALIA Publications (Fundaci\u00f3n TECNALIA Research & Innovation)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210113430","host_organization_name":"Tecnalia","host_organization_lineage":["https://openalex.org/I4210113430"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"journal article"},{"id":"pmh:oai:spiral.imperial.ac.uk:10044/1/103161","is_oa":true,"landing_page_url":"http://hdl.handle.net/10044/1/103161","pdf_url":null,"source":{"id":"https://openalex.org/S4306401396","display_name":"Spiral (Imperial College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I47508984","host_organization_name":"Imperial College London","host_organization_lineage":["https://openalex.org/I47508984"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":{"id":"doi:10.1007/s12559-023-10126-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12559-023-10126-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12559-023-10126-7.pdf","source":{"id":"https://openalex.org/S133078663","display_name":"Cognitive Computation","issn_l":"1866-9956","issn":["1866-9956","1866-9964"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cognitive Computation","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","score":0.41999998688697815,"display_name":"Partnerships for the goals"}],"awards":[{"id":"https://openalex.org/G1285418384","display_name":null,"funder_award_id":"IECNSFC211235","funder_id":"https://openalex.org/F4320320006","funder_display_name":"Royal Society"},{"id":"https://openalex.org/G1342822775","display_name":"Rapid analysis of regional myocardial strain from accelerated velocity-encoded MRI data acquisition for early diagnosis of cardiac disease. ,","funder_award_id":"TG/18/5/34111","funder_id":"https://openalex.org/F4320319992","funder_display_name":"British Heart Foundation"},{"id":"https://openalex.org/G2060262717","display_name":"Combined compressed sensing and super-resolution for 3D late enhancement imaging improves scar segmentation and quantification in atrial fibrillation","funder_award_id":"PG/16/78/32402","funder_id":"https://openalex.org/F4320319992","funder_display_name":"British Heart Foundation"},{"id":"https://openalex.org/G207202694","display_name":null,"funder_award_id":"MC_PC_21013","funder_id":"https://openalex.org/F4320334626","funder_display_name":"Medical Research Council"},{"id":"https://openalex.org/G2815583656","display_name":null,"funder_award_id":"101005122","funder_id":"https://openalex.org/F4320326631","funder_display_name":"Innovative Medicines Initiative"},{"id":"https://openalex.org/G6756521213","display_name":null,"funder_award_id":"MR/V023799/1","funder_id":"https://openalex.org/F4320314731","funder_display_name":"UK Research and Innovation"},{"id":"https://openalex.org/G7986630670","display_name":null,"funder_award_id":"952172","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"}],"funders":[{"id":"https://openalex.org/F4320314731","display_name":"UK Research and Innovation","ror":"https://ror.org/001aqnf71"},{"id":"https://openalex.org/F4320319992","display_name":"British Heart Foundation","ror":"https://ror.org/02wdwnk04"},{"id":"https://openalex.org/F4320320006","display_name":"Royal Society","ror":"https://ror.org/03wnrjx87"},{"id":"https://openalex.org/F4320326631","display_name":"Innovative Medicines Initiative","ror":"https://ror.org/019af4n30"},{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320334626","display_name":"Medical Research Council","ror":"https://ror.org/03x94j517"},{"id":"https://openalex.org/F4320336039","display_name":"NIHR Imperial Biomedical Research Centre","ror":"https://ror.org/01kmhx639"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4322495747.pdf"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W1641498739","https://openalex.org/W1903029394","https://openalex.org/W2395611524","https://openalex.org/W2499316477","https://openalex.org/W2521587260","https://openalex.org/W2598666589","https://openalex.org/W2613041730","https://openalex.org/W2751069891","https://openalex.org/W2766374659","https://openalex.org/W2792124446","https://openalex.org/W2796152334","https://openalex.org/W2884585870","https://openalex.org/W2890460985","https://openalex.org/W2891994532","https://openalex.org/W2910094941","https://openalex.org/W2963046541","https://openalex.org/W2963120588","https://openalex.org/W2963495494","https://openalex.org/W2989562257","https://openalex.org/W3016489761","https://openalex.org/W3017153481","https://openalex.org/W3028279406","https://openalex.org/W3098715541","https://openalex.org/W3101333263","https://openalex.org/W3121099788","https://openalex.org/W3128646645","https://openalex.org/W3135185854","https://openalex.org/W3140895867","https://openalex.org/W3142164167","https://openalex.org/W3142717613","https://openalex.org/W3164178104","https://openalex.org/W3164454234","https://openalex.org/W3168236164","https://openalex.org/W3185052070","https://openalex.org/W3189411510","https://openalex.org/W3201549749","https://openalex.org/W3201574729","https://openalex.org/W3203480968","https://openalex.org/W3204177259","https://openalex.org/W3212386989","https://openalex.org/W4206953207","https://openalex.org/W4212875960","https://openalex.org/W4220968117","https://openalex.org/W4225658221","https://openalex.org/W4225913571","https://openalex.org/W4226045812","https://openalex.org/W4226334005","https://openalex.org/W4283694737","https://openalex.org/W4284975674","https://openalex.org/W4285505553","https://openalex.org/W4287225447","https://openalex.org/W4294605033","https://openalex.org/W4296033473","https://openalex.org/W4307355928","https://openalex.org/W4309635395","https://openalex.org/W6758047254"],"related_works":["https://openalex.org/W3027020613","https://openalex.org/W2016533837","https://openalex.org/W3167885074","https://openalex.org/W2892386716","https://openalex.org/W4386858688","https://openalex.org/W2982536526","https://openalex.org/W4380302312","https://openalex.org/W3008689640","https://openalex.org/W4385338604","https://openalex.org/W3081626085"],"abstract_inverted_index":{"Automated":[0],"segmentation":[1,71,93,182],"of":[2,53,63,99,150],"multiple":[3],"organs":[4,34],"and":[5,17,30,37,46,57,94,103,119,134,153,158,176,189],"tumors":[6],"from":[7],"3D":[8,68,78,167,203],"medical":[9,69,193],"images":[10],"such":[11,141],"as":[12,142],"magnetic":[13],"resonance":[14],"imaging":[15],"(MRI)":[16],"computed":[18],"tomography":[19],"(CT)":[20],"scans":[21],"using":[22],"deep":[23],"learning":[24],"methods":[25,191],"can":[26,135],"aid":[27],"in":[28,107],"diagnosing":[29],"treating":[31],"cancer.":[32],"However,":[33],"often":[35],"overlap":[36],"are":[38,105],"complexly":[39],"connected,":[40],"characterized":[41],"by":[42],"extensive":[43],"anatomical":[44],"variation":[45],"low":[47],"contrast.":[48],"In":[49,73],"addition,":[50],"the":[51,61,108,126,131,148,155,164,201],"diversity":[52],"tumor":[54,95],"shape,":[55],"location,":[56],"appearance,":[58],"coupled":[59],"with":[60],"dominance":[62],"background":[64],"voxels,":[65],"makes":[66],"accurate":[67,91],"image":[70,194],"difficult.":[72],"this":[74],"paper,":[75],"a":[76],"novel":[77],"large-kernel":[79],"(LK)":[80],"attention":[81,111,205],"module":[82,123,206],"is":[83],"proposed":[84,109,202],"to":[85,89,129,186,200],"address":[86],"these":[87],"problems":[88],"achieve":[90],"multi-organ":[92],"segmentation.":[96,195],"The":[97,122,196],"advantages":[98],"biologically":[100],"inspired":[101],"self-attention":[102],"convolution":[104,128],"combined":[106],"LK":[110,127,168,204],"module,":[112],"including":[113],"local":[114],"contextual":[115],"information,":[116],"long-range":[117],"dependencies,":[118],"channel":[120],"adaptation.":[121],"also":[124],"decomposes":[125],"optimize":[130],"computational":[132],"cost":[133],"be":[136],"easily":[137],"incorporated":[138],"into":[139],"CNNs":[140],"U-Net.":[143],"Comprehensive":[144],"ablation":[145],"experiments":[146],"demonstrated":[147],"feasibility":[149],"convolutional":[151],"decomposition":[152],"explored":[154],"most":[156],"efficient":[157],"effective":[159],"network":[160,171],"design.":[161],"Among":[162],"them,":[163],"best":[165],"Mid-type":[166],"attention-based":[169],"U-Net":[170],"was":[172,207],"evaluated":[173],"on":[174],"CT-ORG":[175],"BraTS":[177],"2020":[178],"datasets,":[179],"achieving":[180],"state-of-the-art":[181],"performance":[183,197],"when":[184],"compared":[185],"avant-garde":[187],"CNN":[188],"Transformer-based":[190],"for":[192],"improvement":[198],"due":[199],"statistically":[208],"validated.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":13},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
