{"id":"https://openalex.org/W2592958993","doi":"https://doi.org/10.22489/cinc.2016.028-224","title":"A Novel Left Ventricular Volumes Prediction Method Based on Deep Learning Network in Cardiac MRI","display_name":"A Novel Left Ventricular Volumes Prediction Method Based on Deep Learning Network in Cardiac MRI","publication_year":2016,"publication_date":"2016-09-14","ids":{"openalex":"https://openalex.org/W2592958993","doi":"https://doi.org/10.22489/cinc.2016.028-224","mag":"2592958993"},"language":"en","primary_location":{"id":"doi:10.22489/cinc.2016.028-224","doi":"https://doi.org/10.22489/cinc.2016.028-224","is_oa":true,"landing_page_url":"https://doi.org/10.22489/cinc.2016.028-224","pdf_url":"https://doi.org/10.22489/cinc.2016.028-224","source":{"id":"https://openalex.org/S4220650825","display_name":"Computing in cardiology","issn_l":"2325-887X","issn":["2325-887X","2325-8861"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Computing in Cardiology Conference (CinC)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.22489/cinc.2016.028-224","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091843570","display_name":"Gongning Luo","orcid":"https://orcid.org/0000-0003-3662-0335","observed_orcids":["https://orcid.org/0000-0003-3662-0335"]},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gongning Luo","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088027106","display_name":"Guanxiong Sun","orcid":"https://orcid.org/0000-0003-1901-9097","observed_orcids":["https://orcid.org/0000-0003-1901-9097"]},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanxiong Sun","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049558861","display_name":"Kuanquan Wang","orcid":"https://orcid.org/0000-0003-1347-3491","observed_orcids":["https://orcid.org/0000-0003-1347-3491"]},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kuanquan Wang","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024430250","display_name":"Suyu Dong","orcid":"https://orcid.org/0000-0001-7521-8782","observed_orcids":["https://orcid.org/0000-0001-7521-8782"]},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Suyu Dong","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043271142","display_name":"Henggui Zhang","orcid":"https://orcid.org/0000-0002-0863-5807","observed_orcids":["https://orcid.org/0000-0002-0863-5807","https://orcid.org/0009-0005-8447-7555"]},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]},{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["CN","GB"],"is_corresponding":false,"raw_author_name":"Henggui Zhang","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China","University of Manchester, Manchester, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]},{"raw_affiliation_string":"University of Manchester, Manchester, UK","institution_ids":["https://openalex.org/I28407311"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.6215,"has_fulltext":true,"cited_by_count":39,"citation_normalized_percentile":{"value":0.98934717,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"43","issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10372","display_name":"Cardiac Imaging and Diagnostics","score":0.47530001401901245,"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"}},"topics":[{"id":"https://openalex.org/T10372","display_name":"Cardiac Imaging and Diagnostics","score":0.47530001401901245,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.2556000053882599,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.07729999721050262,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/left-ventricular-volume-estimation","display_name":"left ventricular volume estimation","score":0.9449999928474426},{"id":"https://openalex.org/keywords/cardiac-mri","display_name":"cardiac MRI","score":0.9750000238418579},{"id":"https://openalex.org/keywords/deep-learning","display_name":"deep learning","score":0.6909999847412109},{"id":"https://openalex.org/keywords/heart-disease-diagnosis","display_name":"heart disease diagnosis","score":0.7350000143051147}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5656181573867798},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5621230006217957},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.543599009513855},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.3530312180519104},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.255411833524704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.22489/cinc.2016.028-224","doi":"https://doi.org/10.22489/cinc.2016.028-224","is_oa":true,"landing_page_url":"https://doi.org/10.22489/cinc.2016.028-224","pdf_url":"https://doi.org/10.22489/cinc.2016.028-224","source":{"id":"https://openalex.org/S4220650825","display_name":"Computing in cardiology","issn_l":"2325-887X","issn":["2325-887X","2325-8861"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Computing in Cardiology Conference (CinC)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.22489/cinc.2016.028-224","doi":"https://doi.org/10.22489/cinc.2016.028-224","is_oa":true,"landing_page_url":"https://doi.org/10.22489/cinc.2016.028-224","pdf_url":"https://doi.org/10.22489/cinc.2016.028-224","source":{"id":"https://openalex.org/S4220650825","display_name":"Computing in cardiology","issn_l":"2325-887X","issn":["2325-887X","2325-8861"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Computing in Cardiology Conference (CinC)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8371999859809875,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G8882164163","display_name":"\u57fa\u4e8e3D\u7535-\u529b\u8026\u5408\u4eba\u5fc3\u5ba4\u6a21\u578b\u7684\u751f\u7269\u8d77\u640f\u5668\u673a\u5236\u7814\u7a76","funder_award_id":"61572152","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G903721460","display_name":"\u4e2a\u4f53\u5316\u7684\u865a\u62df\u751f\u7406\u5fc3\u5ba4\u5efa\u6a21\u4e0e\u4eff\u771f\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61571165","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2592958993.pdf","grobid_xml":"https://content.openalex.org/works/W2592958993.grobid-xml"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W1038736503","https://openalex.org/W1987512289","https://openalex.org/W2071151688","https://openalex.org/W2148516227","https://openalex.org/W2149309532","https://openalex.org/W2253429366","https://openalex.org/W2255189008","https://openalex.org/W2274227799","https://openalex.org/W2288468138","https://openalex.org/W2343881908","https://openalex.org/W2511065100","https://openalex.org/W2592024705","https://openalex.org/W2593223207","https://openalex.org/W2593690483","https://openalex.org/W4200084300"],"related_works":["https://openalex.org/W2577762311","https://openalex.org/W2594796721","https://openalex.org/W2993564017","https://openalex.org/W2891835161","https://openalex.org/W2761615849","https://openalex.org/W4230986317","https://openalex.org/W3011573465","https://openalex.org/W2785355525","https://openalex.org/W4238098531","https://openalex.org/W2914645392"],"abstract_inverted_index":{"Accurate":[0],"estimation":[1],"of":[2,14,20,28,33,37,123],"left":[3],"ventricle":[4],"(LV)":[5],"volumes":[6,23,61,96],"plays":[7],"an":[8],"essential":[9],"role":[10],"in":[11,87,118],"clinical":[12,119],"diagnosis":[13,120],"cardiac":[15,75,124],"diseases":[16],"using":[17],"MRI.Conventional":[18],"methods":[19],"estimating":[21],"ventricular":[22],"depend":[24],"on":[25],"the":[26,72,80,93,101,107],"results":[27,90,104],"manual":[29,35],"or":[30],"automatic":[31,46],"segmentation":[32,36,47],"MRI.However,":[34],"MRI":[38,76],"sequences":[39],"is":[40,48],"extremely":[41],"timeconsuming":[42],"and":[43,45,71,116,121],"subjective,":[44],"still":[49],"a":[50,58],"challenging":[51],"task.Therefore,":[52],"this":[53],"study":[54],"aims":[55],"to":[56,113],"develop":[57],"new":[59],"LV":[60,95],"prediction":[62],"method":[63,109],"without":[64],"segmentation,":[65],"motivated":[66],"by":[67],"deep":[68],"learning":[69],"technology":[70],"large":[73],"scale":[74],"(CMR)":[77],"datasets":[78],"from":[79],"second":[81],"Annual":[82],"Data":[83],"Science":[84],"Bowl":[85],"(ADSB)":[86],"2016.The":[88],"experiments":[89],"shows":[91],"that":[92,106],"predicted":[94],"have":[97],"high":[98],"correlation":[99],"with":[100],"ground":[102],"truth.These":[103],"prove":[105],"proposed":[108],"has":[110],"big":[111],"potential":[112],"be":[114],"researched":[115],"applied":[117],"screening":[122],"diseases.":[125]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":4}],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2017-03-16T00:00:00"}