{"id":"https://openalex.org/W4311027595","doi":"https://doi.org/10.3389/frai.2022.1059007","title":"DeepHeartCT: A fully automatic artificial intelligence hybrid framework based on convolutional neural network and multi-atlas segmentation for multi-structure cardiac computed tomography angiography image segmentation","display_name":"DeepHeartCT: A fully automatic artificial intelligence hybrid framework based on convolutional neural network and multi-atlas segmentation for multi-structure cardiac computed tomography angiography image segmentation","publication_year":2022,"publication_date":"2022-11-22","ids":{"openalex":"https://openalex.org/W4311027595","doi":"https://doi.org/10.3389/frai.2022.1059007","pmid":"https://pubmed.ncbi.nlm.nih.gov/36483981"},"language":"en","primary_location":{"id":"doi:10.3389/frai.2022.1059007","is_oa":true,"landing_page_url":"https://doi.org/10.3389/frai.2022.1059007","pdf_url":"https://www.frontiersin.org/articles/10.3389/frai.2022.1059007/pdf","source":{"id":"https://openalex.org/S4210197006","display_name":"Frontiers in Artificial Intelligence","issn_l":"2624-8212","issn":["2624-8212"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/articles/10.3389/frai.2022.1059007/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009773815","display_name":"Vy Bui","orcid":"https://orcid.org/0000-0003-0620-7312"},"institutions":[{"id":"https://openalex.org/I1299303238","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238"]},{"id":"https://openalex.org/I4210106489","display_name":"National Heart Lung and Blood Institute","ror":"https://ror.org/012pb6c26","country_code":"US","type":"facility","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210106489"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vy Bui","raw_affiliation_strings":["National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, United States","institution_ids":["https://openalex.org/I1299303238","https://openalex.org/I4210106489"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044993271","display_name":"Li\u2010Yueh Hsu","orcid":"https://orcid.org/0000-0002-0826-7290"},"institutions":[{"id":"https://openalex.org/I4210155647","display_name":"National Institutes of Health Clinical Center","ror":"https://ror.org/04vfsmv21","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210155647"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Li-Yueh Hsu","raw_affiliation_strings":["Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, United States","institution_ids":["https://openalex.org/I4210155647"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059247040","display_name":"Lin\u2010Ching Chang","orcid":"https://orcid.org/0000-0002-7780-5742"},"institutions":[{"id":"https://openalex.org/I168959743","display_name":"University of America","ror":"https://ror.org/03s0c9350","country_code":"US","type":"education","lineage":["https://openalex.org/I168959743"]},{"id":"https://openalex.org/I84470341","display_name":"Catholic University of America","ror":"https://ror.org/047yk3s18","country_code":"US","type":"education","lineage":["https://openalex.org/I84470341"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lin-Ching Chang","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, United States","institution_ids":["https://openalex.org/I168959743","https://openalex.org/I84470341"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109581339","display_name":"A. Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I1299303238","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238"]},{"id":"https://openalex.org/I168959743","display_name":"University of America","ror":"https://ror.org/03s0c9350","country_code":"US","type":"education","lineage":["https://openalex.org/I168959743"]},{"id":"https://openalex.org/I4210106489","display_name":"National Heart Lung and Blood Institute","ror":"https://ror.org/012pb6c26","country_code":"US","type":"facility","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210106489"]},{"id":"https://openalex.org/I84470341","display_name":"Catholic University of America","ror":"https://ror.org/047yk3s18","country_code":"US","type":"education","lineage":["https://openalex.org/I84470341"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"An-Yu Sun","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, United States","National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, United States","institution_ids":["https://openalex.org/I168959743","https://openalex.org/I84470341"]},{"raw_affiliation_string":"National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, United States","institution_ids":["https://openalex.org/I1299303238","https://openalex.org/I4210106489"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077602332","display_name":"Loc Tran","orcid":"https://orcid.org/0000-0002-0108-503X"},"institutions":[{"id":"https://openalex.org/I1299303238","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238"]},{"id":"https://openalex.org/I168959743","display_name":"University of America","ror":"https://ror.org/03s0c9350","country_code":"US","type":"education","lineage":["https://openalex.org/I168959743"]},{"id":"https://openalex.org/I4210106489","display_name":"National Heart Lung and Blood Institute","ror":"https://ror.org/012pb6c26","country_code":"US","type":"facility","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210106489"]},{"id":"https://openalex.org/I84470341","display_name":"Catholic University of America","ror":"https://ror.org/047yk3s18","country_code":"US","type":"education","lineage":["https://openalex.org/I84470341"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Loc Tran","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, United States","National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, United States","institution_ids":["https://openalex.org/I168959743","https://openalex.org/I84470341"]},{"raw_affiliation_string":"National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, United States","institution_ids":["https://openalex.org/I1299303238","https://openalex.org/I4210106489"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114025336","display_name":"Sujata M. Shanbhag","orcid":null},"institutions":[{"id":"https://openalex.org/I1299303238","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238"]},{"id":"https://openalex.org/I4210106489","display_name":"National Heart Lung and Blood Institute","ror":"https://ror.org/012pb6c26","country_code":"US","type":"facility","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210106489"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sujata M. Shanbhag","raw_affiliation_strings":["National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, United States","institution_ids":["https://openalex.org/I1299303238","https://openalex.org/I4210106489"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102887613","display_name":"Wunan Zhou","orcid":"https://orcid.org/0000-0003-0731-9287"},"institutions":[{"id":"https://openalex.org/I1299303238","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238"]},{"id":"https://openalex.org/I4210106489","display_name":"National Heart Lung and Blood Institute","ror":"https://ror.org/012pb6c26","country_code":"US","type":"facility","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210106489"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wunan Zhou","raw_affiliation_strings":["National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, United States","institution_ids":["https://openalex.org/I1299303238","https://openalex.org/I4210106489"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037356234","display_name":"Nehal N. Mehta","orcid":"https://orcid.org/0000-0003-4939-5130"},"institutions":[{"id":"https://openalex.org/I1299303238","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238"]},{"id":"https://openalex.org/I4210106489","display_name":"National Heart Lung and Blood Institute","ror":"https://ror.org/012pb6c26","country_code":"US","type":"facility","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210106489"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nehal N. Mehta","raw_affiliation_strings":["National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, United States","institution_ids":["https://openalex.org/I1299303238","https://openalex.org/I4210106489"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086010156","display_name":"Marcus Y. Chen","orcid":"https://orcid.org/0000-0003-0743-9369"},"institutions":[{"id":"https://openalex.org/I1299303238","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238"]},{"id":"https://openalex.org/I4210106489","display_name":"National Heart Lung and Blood Institute","ror":"https://ror.org/012pb6c26","country_code":"US","type":"facility","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210106489"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marcus Y. Chen","raw_affiliation_strings":["National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, United States","institution_ids":["https://openalex.org/I1299303238","https://openalex.org/I4210106489"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5044993271"],"corresponding_institution_ids":["https://openalex.org/I4210155647"],"apc_list":{"value":2125,"currency":"USD","value_usd":2125},"apc_paid":{"value":2125,"currency":"USD","value_usd":2125},"fwci":0.3573,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.49186576,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"5","issue":null,"first_page":"1059007","last_page":"1059007"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9941999912261963,"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"}},"topics":[{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9941999912261963,"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":0.9937000274658203,"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":0.9919000267982483,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.764590322971344},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7495251893997192},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7294687628746033},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6439391374588013},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6129279732704163},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5466731786727905},{"id":"https://openalex.org/keywords/hausdorff-distance","display_name":"Hausdorff distance","score":0.4787249267101288},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47357377409935},{"id":"https://openalex.org/keywords/computed-tomography-angiography","display_name":"Computed tomography angiography","score":0.41397589445114136},{"id":"https://openalex.org/keywords/angiography","display_name":"Angiography","score":0.36619436740875244},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32664114236831665},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.30438101291656494},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.24589300155639648}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.764590322971344},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7495251893997192},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7294687628746033},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6439391374588013},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6129279732704163},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5466731786727905},{"id":"https://openalex.org/C141898687","wikidata":"https://www.wikidata.org/wiki/Q1501997","display_name":"Hausdorff distance","level":2,"score":0.4787249267101288},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47357377409935},{"id":"https://openalex.org/C2781347138","wikidata":"https://www.wikidata.org/wiki/Q1024492","display_name":"Computed tomography angiography","level":3,"score":0.41397589445114136},{"id":"https://openalex.org/C2780643987","wikidata":"https://www.wikidata.org/wiki/Q468414","display_name":"Angiography","level":2,"score":0.36619436740875244},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32664114236831665},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.30438101291656494},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.24589300155639648}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3389/frai.2022.1059007","is_oa":true,"landing_page_url":"https://doi.org/10.3389/frai.2022.1059007","pdf_url":"https://www.frontiersin.org/articles/10.3389/frai.2022.1059007/pdf","source":{"id":"https://openalex.org/S4210197006","display_name":"Frontiers in Artificial Intelligence","issn_l":"2624-8212","issn":["2624-8212"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence","raw_type":"journal-article"},{"id":"pmid:36483981","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36483981","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":"Frontiers in artificial intelligence","raw_type":null},{"id":"pmh:oai:doaj.org/article:4c1b52f061eb4984a8beb1e1b2e234e9","is_oa":true,"landing_page_url":"https://doaj.org/article/4c1b52f061eb4984a8beb1e1b2e234e9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Artificial Intelligence, Vol 5 (2022)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:9723331","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9723331","pdf_url":null,"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":"Front Artif Intell","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3389/frai.2022.1059007","is_oa":true,"landing_page_url":"https://doi.org/10.3389/frai.2022.1059007","pdf_url":"https://www.frontiersin.org/articles/10.3389/frai.2022.1059007/pdf","source":{"id":"https://openalex.org/S4210197006","display_name":"Frontiers in Artificial Intelligence","issn_l":"2624-8212","issn":["2624-8212"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.5199999809265137,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337376","display_name":"NIH Clinical Center","ror":"https://ror.org/04vfsmv21"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4311027595.pdf"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W21976314","https://openalex.org/W1522301498","https://openalex.org/W1549847950","https://openalex.org/W1873082310","https://openalex.org/W1901129140","https://openalex.org/W2006466436","https://openalex.org/W2016974693","https://openalex.org/W2040149488","https://openalex.org/W2118246710","https://openalex.org/W2125637308","https://openalex.org/W2160153825","https://openalex.org/W2291593693","https://openalex.org/W2464708700","https://openalex.org/W2533800772","https://openalex.org/W2594608309","https://openalex.org/W2790572202","https://openalex.org/W2792094010","https://openalex.org/W2793788053","https://openalex.org/W2804247377","https://openalex.org/W2806205522","https://openalex.org/W2890653614","https://openalex.org/W2899771611","https://openalex.org/W2913292358","https://openalex.org/W2941049249","https://openalex.org/W2953228371","https://openalex.org/W2963536842","https://openalex.org/W2966333895","https://openalex.org/W2980097659","https://openalex.org/W3000108223","https://openalex.org/W3036586801","https://openalex.org/W3041601596","https://openalex.org/W3091403851","https://openalex.org/W3091785623","https://openalex.org/W3096243711","https://openalex.org/W3103200644","https://openalex.org/W3122718941","https://openalex.org/W3130872505","https://openalex.org/W4205271301","https://openalex.org/W4226334909","https://openalex.org/W6600915255","https://openalex.org/W6631190155","https://openalex.org/W6639352654","https://openalex.org/W6639824700","https://openalex.org/W6748498557","https://openalex.org/W6749718306","https://openalex.org/W6749923946","https://openalex.org/W6755020330","https://openalex.org/W6756040250","https://openalex.org/W6780997208"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W2181259926","https://openalex.org/W2060344285","https://openalex.org/W2884369361","https://openalex.org/W186610043"],"abstract_inverted_index":{"Cardiac":[0],"computed":[1],"tomography":[2],"angiography":[3],"(CTA)":[4],"is":[5],"an":[6],"emerging":[7],"imaging":[8,353],"modality":[9],"for":[10,52,81,180,349],"assessing":[11],"coronary":[12],"artery":[13],"as":[14,16],"well":[15,310],"various":[17,106],"cardiovascular":[18,107],"structures.":[19,283],"Recently,":[20],"deep":[21,185],"learning":[22],"(DL)":[23],"methods":[24],"have":[25],"been":[26],"successfully":[27],"applied":[28],"to":[29,58,61,70,104,153,171,202,236,289],"many":[30],"applications":[31],"of":[32,47,161,183,251,262,274],"medical":[33,352],"image":[34],"analysis":[35],"including":[36,109],"cardiac":[37,85,193,341],"CTA":[38,86,194,342],"structure":[39],"segmentation.":[40],"However,":[41],"DL":[42],"requires":[43],"a":[44,72,97,147,177,184,246,257,269,298,314,324],"large":[45,98,178,191,301],"amounts":[46],"data":[48],"and":[49,83,111,117,122,204,230,268,339],"high-quality":[50,133],"labels":[51,103,135,175,220],"training":[53,182,317,327],"which":[54],"can":[55,345],"be":[56,346],"burdensome":[57],"obtain":[59],"due":[60],"its":[62],"labor-intensive":[63],"nature.":[64],"In":[65,145],"this":[66],"study,":[67],"we":[68],"aim":[69],"develop":[71],"fully":[73],"automatic":[74],"artificial":[75],"intelligence":[76],"(AI)":[77],"system,":[78],"named":[79],"DeepHeartCT,":[80],"accurate":[82,338],"rapid":[84,340],"segmentation":[87,156,239,343],"based":[88,142],"on":[89,214,313],"DL.":[90],"The":[91,208,225,241,303],"proposed":[92,152,242,292,334],"system":[93,128],"was":[94,129,151,211,287],"trained":[95,130,209,296,312],"using":[96,132],"clinical":[99,192],"dataset":[100,179,217,318],"with":[101,218,297,323],"computer-generated":[102,174],"segment":[105],"structures":[108],"left":[110,116],"right":[112,118],"ventricles":[113],"(LV,":[114],"RV),":[115],"atria":[119],"(LA,":[120],"RA),":[121],"LV":[123],"myocardium":[124],"(LVM).":[125],"This":[126,165],"new":[127,169],"directly":[131],"computer":[134],"generated":[136],"from":[137,176],"our":[138,206,306],"previously":[139],"developed":[140],"multi-atlas":[141],"AI":[143,294],"system.":[144],"addition,":[146],"reverse":[148],"ranking":[149],"strategy":[150,166],"assess":[154],"the":[155,159,168,238,291,333],"quality":[157],"in":[158],"absence":[160],"manual":[162,219],"reference":[163],"labels.":[164],"allowed":[167],"framework":[170,244,295,307,336],"assemble":[172],"optimal":[173,316],"effective":[181],"convolutional":[186],"neural":[187],"network":[188],"(CNN).":[189],"A":[190],"studies":[195],"(":[196,221,319],"n":[197,222,320],"=":[198,223,321],"1,064)":[199],"were":[200,234],"used":[201,235],"train":[203],"validate":[205],"framework.":[207],"model":[210],"then":[212],"tested":[213],"another":[215],"independent":[216],"60).":[224],"Dice":[226,249],"score,":[227],"Hausdorff":[228,260],"distance":[229,233,261,273],"mean":[231,271],"surface":[232,272],"quantify":[237],"accuracy.":[240],"DeepHeartCT":[243,335],"yields":[245],"high":[247],"median":[248,259],"score":[250],"0.90":[252],"[interquartile":[253],"range":[254],"(IQR),":[255],"0.90\u20130.91],":[256],"low":[258,270],"7":[263],"mm":[264,276],"(IQR,":[265,277],"4\u201315":[266],"mm)":[267,279],"0.80":[275],"0.57\u20131.29":[278],"across":[280],"all":[281],"segmented":[282],"An":[284],"additional":[285],"experiment":[286],"conducted":[288],"evaluate":[290],"DL-based":[293],"small":[299,315],"vs.":[300],"dataset.":[302],"results":[304,330],"show":[305],"also":[308],"performed":[309],"when":[311],"110)":[322],"significantly":[325],"reduced":[326],"time.":[328],"These":[329],"demonstrated":[331],"that":[332,344],"provides":[337],"readily":[347],"generalized":[348],"handling":[350],"large-scale":[351],"applications.":[354]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}
