{"id":"https://openalex.org/W3040786357","doi":"https://doi.org/10.1109/access.2020.3008190","title":"Automatic Epicardial Fat Segmentation and Quantification of CT Scans Using Dual U-Nets With a Morphological Processing Layer","display_name":"Automatic Epicardial Fat Segmentation and Quantification of CT Scans Using Dual U-Nets With a Morphological Processing Layer","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3040786357","doi":"https://doi.org/10.1109/access.2020.3008190","mag":"3040786357"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3008190","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3008190","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09137693.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09137693.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100360241","display_name":"Qi Zhang","orcid":"https://orcid.org/0000-0001-9595-5640"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":true,"raw_author_name":"Qi Zhang","raw_affiliation_strings":["Department of Computer and Information Science, PAMI Research Group, Faculty of Science and Technology, University of Macau, Taipa, Macau"],"raw_orcid":"https://orcid.org/0000-0001-9595-5640","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, PAMI Research Group, Faculty of Science and Technology, University of Macau, Taipa, Macau","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091707052","display_name":"Jianhang Zhou","orcid":"https://orcid.org/0000-0002-2423-2311"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Jianhang Zhou","raw_affiliation_strings":["Department of Computer and Information Science, PAMI Research Group, Faculty of Science and Technology, University of Macau, Taipa, Macau"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, PAMI Research Group, Faculty of Science and Technology, University of Macau, Taipa, Macau","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048088901","display_name":"Bob Zhang","orcid":"https://orcid.org/0000-0003-2497-9519"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Bob Zhang","raw_affiliation_strings":["Department of Computer and Information Science, PAMI Research Group, Faculty of Science and Technology, University of Macau, Taipa, Macau"],"raw_orcid":"https://orcid.org/0000-0003-2497-9519","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, PAMI Research Group, Faculty of Science and Technology, University of Macau, Taipa, Macau","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109574954","display_name":"Weijia Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weijia Jia","raw_affiliation_strings":["BNU-UIC Joint AI Research Institute, Beijing Normal University, Zhuhai, China"],"raw_orcid":"https://orcid.org/0000-0001-5628-6237","affiliations":[{"raw_affiliation_string":"BNU-UIC Joint AI Research Institute, Beijing Normal University, Zhuhai, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013119881","display_name":"Enhua Wu","orcid":"https://orcid.org/0000-0002-2174-1428"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Enhua Wu","raw_affiliation_strings":["Faculty of Science and Technology, University of Macau, Taipa, Macau"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Science and Technology, University of Macau, Taipa, Macau","institution_ids":["https://openalex.org/I204512498"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100360241"],"corresponding_institution_ids":["https://openalex.org/I204512498"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.9216,"has_fulltext":true,"cited_by_count":41,"citation_normalized_percentile":{"value":0.92537795,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"128032","last_page":"128041"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12979","display_name":"Cardiovascular Disease and Adiposity","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T12979","display_name":"Cardiovascular Disease and Adiposity","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T11457","display_name":"Adipose Tissue and Metabolism","score":0.9009000062942505,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"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/epicardial-fat","display_name":"Epicardial fat","score":0.8025587201118469},{"id":"https://openalex.org/keywords/pericardium","display_name":"Pericardium","score":0.7126325368881226},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6369617581367493},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5817171335220337},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5696980953216553},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.5401225686073303},{"id":"https://openalex.org/keywords/jaccard-index","display_name":"Jaccard index","score":0.5000088214874268},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4842517077922821},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.45461711287498474},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.43536177277565},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2757130563259125},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.16506290435791016},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.15108060836791992},{"id":"https://openalex.org/keywords/adipose-tissue","display_name":"Adipose tissue","score":0.14533212780952454}],"concepts":[{"id":"https://openalex.org/C2908987861","wikidata":"https://www.wikidata.org/wiki/Q193302","display_name":"Epicardial fat","level":3,"score":0.8025587201118469},{"id":"https://openalex.org/C2778875491","wikidata":"https://www.wikidata.org/wiki/Q193302","display_name":"Pericardium","level":2,"score":0.7126325368881226},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6369617581367493},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5817171335220337},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5696980953216553},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.5401225686073303},{"id":"https://openalex.org/C203519979","wikidata":"https://www.wikidata.org/wiki/Q865360","display_name":"Jaccard index","level":3,"score":0.5000088214874268},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4842517077922821},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.45461711287498474},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.43536177277565},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2757130563259125},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.16506290435791016},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.15108060836791992},{"id":"https://openalex.org/C171089720","wikidata":"https://www.wikidata.org/wiki/Q193583","display_name":"Adipose tissue","level":2,"score":0.14533212780952454},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3008190","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3008190","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09137693.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:446c5e90d7fd4570afb39e1a1048f8d9","is_oa":true,"landing_page_url":"https://doaj.org/article/446c5e90d7fd4570afb39e1a1048f8d9","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":"IEEE Access, Vol 8, Pp 128032-128041 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3008190","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3008190","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09137693.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7829160424","display_name":null,"funder_award_id":"MYRG2019-00006-FST","funder_id":"https://openalex.org/F4320322841","funder_display_name":"Universidade de Macau"}],"funders":[{"id":"https://openalex.org/F4320322841","display_name":"Universidade de Macau","ror":"https://ror.org/01r4q9n85"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3040786357.pdf","grobid_xml":"https://content.openalex.org/works/W3040786357.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W247104752","https://openalex.org/W1505353324","https://openalex.org/W1522301498","https://openalex.org/W1534151410","https://openalex.org/W1561442812","https://openalex.org/W1565946331","https://openalex.org/W1856792630","https://openalex.org/W1901129140","https://openalex.org/W1923360934","https://openalex.org/W1967911518","https://openalex.org/W2026394576","https://openalex.org/W2036175283","https://openalex.org/W2037717990","https://openalex.org/W2051175196","https://openalex.org/W2071772893","https://openalex.org/W2088118463","https://openalex.org/W2091338891","https://openalex.org/W2110909360","https://openalex.org/W2115333089","https://openalex.org/W2116044718","https://openalex.org/W2343963065","https://openalex.org/W2585439946","https://openalex.org/W2589664828","https://openalex.org/W2605236239","https://openalex.org/W2756462150","https://openalex.org/W2790564346","https://openalex.org/W2914272101","https://openalex.org/W2922368055","https://openalex.org/W2927851116","https://openalex.org/W2941049249","https://openalex.org/W2944539652","https://openalex.org/W2945454497","https://openalex.org/W2963881378","https://openalex.org/W2964121744","https://openalex.org/W2966823445","https://openalex.org/W2966967545","https://openalex.org/W2979751829","https://openalex.org/W2989991226","https://openalex.org/W2991912488","https://openalex.org/W2999370477","https://openalex.org/W3012214679","https://openalex.org/W3101020973","https://openalex.org/W3198390318","https://openalex.org/W4244003036","https://openalex.org/W6631190155","https://openalex.org/W6639824700"],"related_works":["https://openalex.org/W2953570019","https://openalex.org/W3012828488","https://openalex.org/W4367019122","https://openalex.org/W3116883888","https://openalex.org/W4280645644","https://openalex.org/W2766422710","https://openalex.org/W4287631720","https://openalex.org/W3093926553","https://openalex.org/W4223526259","https://openalex.org/W2033211496"],"abstract_inverted_index":{"The":[0,89,188],"epicardial":[1,69,148,198],"fat":[2,23,39,70,149,199],"plays":[3],"a":[4,60,181],"key":[5],"role":[6],"in":[7,27,40],"the":[8,44,80,95,100,113,117,124,129,132,147,151,156,159,166],"development":[9],"of":[10,68,116,128,150],"many":[11],"cardiovascular":[12],"diseases.":[13],"It":[14],"is":[15,32,52,84,92,110,135,194],"necessary":[16],"and":[17,46,66,122,145],"useful":[18],"to":[19,35,98,120,143,176],"precisely":[20],"segment":[21,37,146],"this":[22,38,56,87],"from":[24,71,155],"CT":[25,72,183],"scans":[26,73],"clinical":[28,41],"studies.":[29],"However,":[30],"it":[31],"not":[33],"feasible":[34],"manually":[36],"practice,":[42],"as":[43,112,140],"workload":[45],"cost":[47],"for":[48,63,86,196],"technicians":[49],"or":[50],"physicians":[51],"quite":[53],"high.":[54],"In":[55,75],"work,":[57],"we":[58],"propose":[59],"novel":[61],"method":[62,164,193],"automatic":[64],"segmentation":[65],"quantification":[67],"accurately.":[74],"detail,":[76],"dual":[77],"U-Nets":[78],"with":[79,185],"morphological":[81,108],"processing":[82],"layer":[83,109,115],"used":[85],"goal.":[88],"first":[90,118,160],"network":[91,134],"based":[93],"on":[94,180],"U-Net":[96,139],"framework":[97],"detect":[99],"pericardium,":[101],"before":[102],"segmenting":[103],"its":[104,141],"inside":[105,126,153],"region.":[106],"A":[107],"concatenated":[111],"following":[114],"network,":[119],"refine":[121],"obtain":[123],"ideal":[125],"region":[127,154],"pericardium.":[130],"While":[131],"second":[133],"also":[136],"applied":[137],"using":[138,158],"backbone":[142],"find":[144],"processed":[152],"pericardium":[157],"network.":[161],"Our":[162],"proposed":[163,192],"obtains":[165],"highest":[167],"mean":[168],"Dice":[169],"similarity":[170],"(91.19%),":[171],"correlation":[172],"coefficient":[173],"(0.9304)":[174],"compared":[175],"other":[177],"state-of-art":[178],"methods":[179],"cardiac":[182],"dataset":[184],"20":[186],"patients.":[187],"results":[189],"indicate":[190],"our":[191],"effective":[195],"quantifying":[197],"automatically.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":6}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}