{"id":"https://openalex.org/W2909466312","doi":"https://doi.org/10.1145/3285996.3286016","title":"Robust Segmentation of the Left Ventricle from Cardiac MRI via Capsule Neural Network","display_name":"Robust Segmentation of the Left Ventricle from Cardiac MRI via Capsule Neural Network","publication_year":2018,"publication_date":"2018-10-13","ids":{"openalex":"https://openalex.org/W2909466312","doi":"https://doi.org/10.1145/3285996.3286016","mag":"2909466312"},"language":"en","primary_location":{"id":"doi:10.1145/3285996.3286016","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3285996.3286016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Symposium on Image Computing and Digital Medicine","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/A5038916831","display_name":"Jiaxiu Dong","orcid":"https://orcid.org/0000-0002-5732-5944"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiaxiu Dong","raw_affiliation_strings":["Zhengzhou University, Zhengzhou, Henan, China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, Henan, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353381","display_name":"Chang Liu","orcid":"https://orcid.org/0009-0001-7457-0204"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chang Liu","raw_affiliation_strings":["Zhengzhou University, Zhengzhou, Henan, China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, Henan, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100669592","display_name":"Cong Yang","orcid":"https://orcid.org/0000-0001-5933-0950"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cong Yang","raw_affiliation_strings":["Zhengzhou University, Zhengzhou, Henan, China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, Henan, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068179622","display_name":"Nan Lin","orcid":"https://orcid.org/0000-0003-1324-1607"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Lin","raw_affiliation_strings":["Zhengzhou University, Zhengzhou, Henan, China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, Henan, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072419341","display_name":"Yangjie Cao","orcid":"https://orcid.org/0000-0002-1170-4340"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangjie Cao","raw_affiliation_strings":["Zhengzhou University, Zhengzhou, Henan, China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, Henan, China","institution_ids":["https://openalex.org/I38877650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5038916831"],"corresponding_institution_ids":["https://openalex.org/I38877650"],"apc_list":null,"apc_paid":null,"fwci":0.2089,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.57668846,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"88","last_page":"91"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9979000091552734,"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":0.9979000091552734,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9847000241279602,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"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":0.9829999804496765,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ventricle","display_name":"Ventricle","score":0.6688681840896606},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5387654304504395},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5288340449333191},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5264029502868652},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.45307374000549316},{"id":"https://openalex.org/keywords/capsule","display_name":"Capsule","score":0.4162828028202057},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.410695344209671},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32925546169281006},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3105030655860901},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.2938871383666992},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.08113875985145569}],"concepts":[{"id":"https://openalex.org/C2778921608","wikidata":"https://www.wikidata.org/wiki/Q2002035","display_name":"Ventricle","level":2,"score":0.6688681840896606},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5387654304504395},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5288340449333191},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5264029502868652},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.45307374000549316},{"id":"https://openalex.org/C2778778583","wikidata":"https://www.wikidata.org/wiki/Q147768","display_name":"Capsule","level":2,"score":0.4162828028202057},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.410695344209671},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32925546169281006},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3105030655860901},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.2938871383666992},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.08113875985145569},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3285996.3286016","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3285996.3286016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Symposium on Image Computing and Digital Medicine","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.8500000238418579,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1156306556","https://openalex.org/W1769974409","https://openalex.org/W1782973594","https://openalex.org/W1966192780","https://openalex.org/W1987512289","https://openalex.org/W2038952578","https://openalex.org/W2104095591","https://openalex.org/W2148826257","https://openalex.org/W2334919579","https://openalex.org/W2337438617","https://openalex.org/W2591232542","https://openalex.org/W2963703618","https://openalex.org/W2970395168","https://openalex.org/W4254369203"],"related_works":["https://openalex.org/W1974950787","https://openalex.org/W2358162314","https://openalex.org/W2357652707","https://openalex.org/W2365313273","https://openalex.org/W2263516560","https://openalex.org/W2365750193","https://openalex.org/W2355255155","https://openalex.org/W4365513328","https://openalex.org/W2372963899","https://openalex.org/W2369519607"],"abstract_inverted_index":{"Segmentation":[0],"of":[1,20,26,46,54,71,116],"the":[2,15,23,47,97,126,137],"left":[3,48,102],"ventricle":[4,103],"from":[5,99],"cardiac":[6],"magnetic":[7],"resonance":[8],"images":[9,112,138],"provides":[10],"important":[11],"supplementary":[12],"information":[13],"for":[14],"diagnosis":[16],"and":[17,41,66,94,131],"treatment":[18],"follow-up":[19],"cardiovascular":[21],"diseases,":[22],"main":[24],"cause":[25],"deaths":[27],"worldwide.":[28],"In":[29],"this":[30],"paper,":[31],"we":[32],"propose":[33],"a":[34],"novel":[35],"capsule":[36,58,61,73],"neural":[37],"network":[38,52],"to":[39,83],"robustly":[40],"accurately":[42],"extract":[43],"myocardial":[44],"borders":[45],"ventricle.":[49],"The":[50,69,89,118],"whole":[51],"consists":[53],"convolutional":[55],"layers,":[56,65],"primary":[57],"layer,":[59,62],"digital":[60,72],"fully":[63],"connected":[64],"de-convolutional":[67],"layers.":[68],"output":[70],"layer":[74],"is":[75,92,129],"generated":[76],"by":[77],"dynamic":[78],"routing,":[79],"enabling":[80],"our":[81,109],"method":[82,91,110,120],"cope":[84],"with":[85,113],"noise":[86],"very":[87,133],"well.":[88],"proposed":[90,119],"trained":[93],"validated":[95],"on":[96,111,125],"data":[98,128],"MICCAI":[100],"2013":[101],"segmentation":[104],"challenge.":[105],"We":[106],"also":[107],"validate":[108],"different":[114],"levels":[115],"noise.":[117],"exhibits":[121],"desirable":[122],"Dice":[123],"coefficient":[124],"origin":[127],"0.9417,":[130],"shows":[132],"little":[134],"decrease":[135],"even":[136],"are":[139],"noised":[140],"heavily.":[141]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}