{"id":"https://openalex.org/W3026073575","doi":"https://doi.org/10.1109/tip.2020.2994445","title":"Multi-Atlas Brain Parcellation Using Squeeze-and-Excitation Fully Convolutional Networks","display_name":"Multi-Atlas Brain Parcellation Using Squeeze-and-Excitation Fully Convolutional Networks","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3026073575","doi":"https://doi.org/10.1109/tip.2020.2994445","mag":"3026073575"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2020.2994445","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.2994445","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-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/A5101553435","display_name":"Zhenyu Tang","orcid":"https://orcid.org/0000-0002-6998-2669"},"institutions":[{"id":"https://openalex.org/I4210165198","display_name":"Beijing Advanced Sciences and Innovation Center","ror":"https://ror.org/05qm21180","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165198"]},{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhenyu Tang","raw_affiliation_strings":["Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I4210165198","https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101669639","display_name":"Xianli Liu","orcid":"https://orcid.org/0000-0002-8023-3036"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianli Liu","raw_affiliation_strings":["School of Computer Science and Technology, Anhui University, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100421442","display_name":"Yang Li","orcid":"https://orcid.org/0000-0002-1751-1742"},"institutions":[{"id":"https://openalex.org/I4210165198","display_name":"Beijing Advanced Sciences and Innovation Center","ror":"https://ror.org/05qm21180","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165198"]},{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Li","raw_affiliation_strings":["Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I4210165198","https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015071060","display_name":"Pew\u2010Thian Yap","orcid":"https://orcid.org/0000-0003-1489-2102"},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pew-Thian Yap","raw_affiliation_strings":["University of North Carolina at Chapel Hill, Chapel Hill, USA"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Chapel Hill, Chapel Hill, USA","institution_ids":["https://openalex.org/I114027177"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000937401","display_name":"Dinggang Shen","orcid":"https://orcid.org/0000-0002-7934-5698"},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]},{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR","US"],"is_corresponding":false,"raw_author_name":"Dinggang Shen","raw_affiliation_strings":["Korea University, Seoul, South Korea","University of North Carolina at Chapel Hill, Chapel Hill, USA"],"affiliations":[{"raw_affiliation_string":"Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"University of North Carolina at Chapel Hill, Chapel Hill, USA","institution_ids":["https://openalex.org/I114027177"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101553435"],"corresponding_institution_ids":["https://openalex.org/I4210165198","https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.9815,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.78038284,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"29","issue":null,"first_page":"6864","last_page":"6872"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9993000030517578,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9993000030517578,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9975000023841858,"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":0.9969000220298767,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8000233173370361},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7437053322792053},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6380066275596619},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6323018670082092},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.585907518863678},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49213093519210815},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.48814019560813904},{"id":"https://openalex.org/keywords/brain-atlas","display_name":"Brain atlas","score":0.46312910318374634},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.4405364990234375},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34995654225349426},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1925678253173828}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8000233173370361},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7437053322792053},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6380066275596619},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6323018670082092},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.585907518863678},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49213093519210815},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.48814019560813904},{"id":"https://openalex.org/C2780972224","wikidata":"https://www.wikidata.org/wiki/Q17047956","display_name":"Brain atlas","level":2,"score":0.46312910318374634},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.4405364990234375},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34995654225349426},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1925678253173828},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tip.2020.2994445","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.2994445","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1667869507","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1910109443","https://openalex.org/W1969257438","https://openalex.org/W1970928383","https://openalex.org/W1987869189","https://openalex.org/W1997677703","https://openalex.org/W1998070036","https://openalex.org/W2013930726","https://openalex.org/W2032377318","https://openalex.org/W2066839705","https://openalex.org/W2083099567","https://openalex.org/W2085091083","https://openalex.org/W2092730500","https://openalex.org/W2099471712","https://openalex.org/W2102099319","https://openalex.org/W2103857226","https://openalex.org/W2128244716","https://openalex.org/W2128806031","https://openalex.org/W2147555557","https://openalex.org/W2148157540","https://openalex.org/W2148347694","https://openalex.org/W2155298532","https://openalex.org/W2160905891","https://openalex.org/W2160992167","https://openalex.org/W2163595993","https://openalex.org/W2441649867","https://openalex.org/W2618530766","https://openalex.org/W2622064152","https://openalex.org/W2751068216","https://openalex.org/W2752782242","https://openalex.org/W2899478482","https://openalex.org/W2957070959","https://openalex.org/W2963196212","https://openalex.org/W2963420686","https://openalex.org/W3101639073","https://openalex.org/W4298771022","https://openalex.org/W4320013936","https://openalex.org/W6639824700","https://openalex.org/W6748542959"],"related_works":["https://openalex.org/W4293202849","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W2060789105"],"abstract_inverted_index":{"Multi-atlas":[0],"parcellation":[1,34,75],"(MAP)":[2],"is":[3,24,92,122,143],"carried":[4],"out":[5],"on":[6,94,160],"a":[7,82,125,131],"brain":[8,17,57,66,88,114,150],"image":[9,163],"by":[10],"propagating":[11],"and":[12,26,46,99,106,156,166],"fusing":[13],"labelled":[14,65],"regions":[15],"from":[16,110,149],"atlases.":[18],"Typical":[19],"nonlinear":[20,41],"registration-based":[21],"label":[22],"propagation":[23],"time-consuming":[25],"sensitive":[27],"to":[28,39,68,116],"inter-subject":[29],"differences.":[30],"Recently,":[31],"deep":[32],"learning":[33],"(DLP)":[35],"has":[36],"been":[37],"proposed":[38],"avoid":[40],"registration":[42],"for":[43,72,87],"better":[44],"efficiency":[45],"robustness":[47],"than":[48],"MAP.":[49],"However,":[50],"most":[51,112],"existing":[52],"DLP":[53,85,158],"methods":[54,159],"neglect":[55],"using":[56],"atlases,":[58,151],"which":[59],"contain":[60],"high-level":[61],"information":[62],"(e.g.,":[63],"manually":[64],"regions),":[67],"provide":[69],"auxiliary":[70],"features":[71,109],"improving":[73],"the":[74,111,146],"accuracy.":[76],"In":[77],"this":[78],"paper,":[79],"we":[80],"propose":[81],"novel":[83],"multi-atlas":[84],"method":[86,91,121,153],"parcellation.":[89,118],"Our":[90],"based":[93],"fully":[95],"convolutional":[96,132],"networks":[97],"(FCN)":[98],"squeeze-and-excitation":[100],"(SE)":[101],"modules.":[102],"It":[103],"can":[104],"automatically":[105],"adaptively":[107],"select":[108],"relevant":[113],"atlases":[115],"guide":[117],"Moreover,":[119],"our":[120,152],"trained":[123],"via":[124],"generative":[126],"adversarial":[127],"network":[128,134],"(GAN),":[129],"where":[130],"neural":[133],"(CNN)":[135],"with":[136],"multi-scale":[137],"l":[138],"<sub":[139],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[140],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[141],"loss":[142],"used":[144],"as":[145],"discriminator.":[147],"Benefiting":[148],"outperforms":[154],"MAP":[155],"state-of-the-art":[157],"two":[161],"public":[162],"datasets":[164],"(LPBA40":[165],"NIREP-NA0).":[167]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-31T07:56:22.981413","created_date":"2025-10-10T00:00:00"}