{"id":"https://openalex.org/W4210791717","doi":"https://doi.org/10.1109/jbhi.2022.3146013","title":"Cascaded Triplanar Autoencoder M-Net for Fully Automatic Segmentation of Left Ventricle Myocardial Scar From Three-Dimensional Late Gadolinium-Enhanced MR Images","display_name":"Cascaded Triplanar Autoencoder M-Net for Fully Automatic Segmentation of Left Ventricle Myocardial Scar From Three-Dimensional Late Gadolinium-Enhanced MR Images","publication_year":2022,"publication_date":"2022-01-25","ids":{"openalex":"https://openalex.org/W4210791717","doi":"https://doi.org/10.1109/jbhi.2022.3146013","pmid":"https://pubmed.ncbi.nlm.nih.gov/35077377"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2022.3146013","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-article","indexed_in":["crossref","pubmed"],"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/A5000776140","display_name":"Mingquan Lin","orcid":"https://orcid.org/0000-0003-0862-6588"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"funder","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Mingquan Lin","raw_affiliation_strings":["Department of Electrical Engineering, City University of Hong Kong, SAR, China"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, City University of Hong Kong, SAR, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075576909","display_name":"Mingjie Jiang","orcid":"https://orcid.org/0000-0001-5384-8994"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"funder","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Mingjie Jiang","raw_affiliation_strings":["Department of Electrical Engineering, City University of Hong Kong, SAR, China"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, City University of Hong Kong, SAR, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061195038","display_name":"Mingbo Zhao","orcid":"https://orcid.org/0000-0003-0381-4360"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"funder","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingbo Zhao","raw_affiliation_strings":["School of Information Science and Technology, Donghua University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044454144","display_name":"Eranga Ukwatta","orcid":"https://orcid.org/0000-0003-0180-4716"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"funder","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Eranga Ukwatta","raw_affiliation_strings":["University of Guelph, Guelph, Ontario, Canada"],"affiliations":[{"raw_affiliation_string":"University of Guelph, Guelph, Ontario, Canada","institution_ids":["https://openalex.org/I79817857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070858953","display_name":"James A. White","orcid":"https://orcid.org/0000-0002-5297-4507"},"institutions":[{"id":"https://openalex.org/I56478863","display_name":"Libin Cardiovascular Institute of Alberta","ror":"https://ror.org/02qthww36","country_code":"CA","type":"facility","lineage":["https://openalex.org/I56478863"]},{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"funder","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"James A. White","raw_affiliation_strings":["Stephenson Cardiac Imaging Centre at the Libin Cardiovascular Institute, University of Calgary, Calgary, Alberta, Canada"],"affiliations":[{"raw_affiliation_string":"Stephenson Cardiac Imaging Centre at the Libin Cardiovascular Institute, University of Calgary, Calgary, Alberta, Canada","institution_ids":["https://openalex.org/I56478863","https://openalex.org/I168635309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051126889","display_name":"Bernard Chiu","orcid":"https://orcid.org/0000-0001-5237-2410"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"funder","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Bernard Chiu","raw_affiliation_strings":["Department of Electrical Engineering, City University of Hong Kong, SAR, China"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, City University of Hong Kong, SAR, China","institution_ids":["https://openalex.org/I168719708"]}]}],"institution_assertions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.999948,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":95},"biblio":{"volume":"26","issue":"6","first_page":"2582","last_page":"2593"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9987,"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9987,"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/T10372","display_name":"Cardiac Imaging and Diagnostics","score":0.9982,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9968,"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/autoencoder","display_name":"Autoencoder","score":0.83233076},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.5940746}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.83233076},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7232766},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.66926247},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6068211},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.5940746},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5656036},{"id":"https://openalex.org/C2778921608","wikidata":"https://www.wikidata.org/wiki/Q2002035","display_name":"Ventricle","level":2,"score":0.51696676},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49817848},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.47764292},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.42262238},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.42093268},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3710801},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32977504},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2669386},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.1917493},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.13800725}],"mesh":[{"descriptor_ui":"D005682","descriptor_name":"Gadolinium","qualifier_ui":"","qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006352","descriptor_name":"Heart Ventricles","qualifier_ui":"","qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D002921","descriptor_name":"Cicatrix","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002921","descriptor_name":"Cicatrix","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D002921","descriptor_name":"Cicatrix","qualifier_ui":"Q000473","qualifier_name":"pathology","is_major_topic":false},{"descriptor_ui":"D006352","descriptor_name":"Heart Ventricles","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D009206","descriptor_name":"Myocardium","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009206","descriptor_name":"Myocardium","qualifier_ui":"Q000473","qualifier_name":"pathology","is_major_topic":false}],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2022.3146013","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35077377","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_indexed_in_scopus":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":["National Institutes of Health"],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[{"funder":"https://openalex.org/F4320309893","funder_display_name":"City University of Hong Kong","award_id":"7005226"},{"funder":"https://openalex.org/F4320309893","funder_display_name":"City University of Hong Kong","award_id":"7005441"}],"datasets":[],"versions":[],"referenced_works_count":50,"referenced_works":["https://openalex.org/W1480256845","https://openalex.org/W1570404261","https://openalex.org/W1767244069","https://openalex.org/W1901129140","https://openalex.org/W1966190213","https://openalex.org/W1969085832","https://openalex.org/W1978087315","https://openalex.org/W1979226691","https://openalex.org/W1986622667","https://openalex.org/W1987015763","https://openalex.org/W1988308001","https://openalex.org/W1988707821","https://openalex.org/W1989443948","https://openalex.org/W1992763477","https://openalex.org/W2011548497","https://openalex.org/W201176276","https://openalex.org/W2019400046","https://openalex.org/W2025362214","https://openalex.org/W2043037509","https://openalex.org/W2080971686","https://openalex.org/W2083823350","https://openalex.org/W2104095591","https://openalex.org/W2110408320","https://openalex.org/W2111848616","https://openalex.org/W2126171519","https://openalex.org/W2127890285","https://openalex.org/W2149632605","https://openalex.org/W2149710008","https://openalex.org/W2153322653","https://openalex.org/W2171177394","https://openalex.org/W2194775991","https://openalex.org/W2201213193","https://openalex.org/W2546752250","https://openalex.org/W2613255783","https://openalex.org/W2624871570","https://openalex.org/W2900827846","https://openalex.org/W2912963483","https://openalex.org/W2964185501","https://openalex.org/W2979448322","https://openalex.org/W2983823075","https://openalex.org/W2988868890","https://openalex.org/W2996131899","https://openalex.org/W3000054715","https://openalex.org/W3090886579","https://openalex.org/W3101507774","https://openalex.org/W3112701542","https://openalex.org/W3172614365","https://openalex.org/W4241501232","https://openalex.org/W6908809","https://openalex.org/W845365781"],"related_works":["https://openalex.org/W4376166922","https://openalex.org/W4362597605","https://openalex.org/W4297676672","https://openalex.org/W4289763776","https://openalex.org/W4281702477","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W2810330923","https://openalex.org/W2490526372","https://openalex.org/W1574414179"],"abstract_inverted_index":{"While":[0],"three-dimensional":[1],"(3D)":[2],"late":[3],"gadolinium-enhanced":[4],"(LGE)":[5],"magnetic":[6],"resonance":[7],"(MR)":[8],"imaging":[9,250],"provides":[10,139,169],"good":[11],"conspicuity":[12],"of":[13,32,97,129,172,233,248],"small":[14],"myocardial":[15,57],"lesions":[16],"with":[17,103],"short":[18],"acquisition":[19],"time,":[20],"it":[21],"poses":[22],"a":[23,29,42,161],"challenge":[24],"for":[25,176,196],"image":[26],"analysis":[27],"as":[28],"large":[30,228],"number":[31],"axial":[33],"images":[34],"are":[35,184],"required":[36,195],"to":[37,55,67,142,165,190,198],"be":[38],"segmented.":[39],"We":[40],"developed":[41],"fully":[43],"automatic":[44],"convolutional":[45],"neural":[46],"network":[47],"(CNN)":[48],"called":[49],"cascaded":[50,66],"triplanar":[51],"autoencoder":[52,87,159],"M-Net":[53],"(CTAEM-Net)":[54],"segment":[56,68,199],"scar":[58,77,180,204],"from":[59,158],"3D":[60,99],"LGE":[61,100],"MRI.":[62],"Two":[63],"sub-networks":[64],"were":[65],"the":[69,76,79,91,98,104,130,185,203,234],"left":[70],"ventricle":[71],"(LV)":[72],"myocardium":[73,178,201],"and":[74,94,121,132,145,174,179,202,209,219],"then":[75],"within":[78],"pre-segmented":[80],"LV":[81,177,200],"myocardium.":[82],"Each":[83],"sub-network":[84],"contains":[85],"three":[86,113],"M-Nets":[88],"(AEM-Nets)":[89],"segmenting":[90],"axial,":[92],"sagittal":[93],"coronal":[95],"slices":[96],"MR":[101,214],"image,":[102],"final":[105],"segmentation":[106,152],"determined":[107],"by":[108,154,222,239],"voting.":[109],"The":[110,124,167,193,217,231],"AEM-Net":[111],"integrates":[112],"features:":[114],"(1)":[115],"multi-scale":[116,125],"inputs,":[117],"(2)":[118],"deep":[119],"supervision":[120,138,141],"(3)":[122],"multi-tasking.":[123],"inputs":[126],"allow":[127],"consideration":[128],"global":[131],"local":[133],"features":[134],"in":[135,243],"segmentation.":[136,166],"Deep":[137],"direct":[140],"deeper":[143],"layers":[144],"facilitates":[146],"CNN":[147],"convergence.":[148],"Multi-task":[149],"learning":[150],"reduces":[151],"overfitting":[153],"acquiring":[155],"additional":[156],"information":[157],"reconstruction,":[160],"task":[162],"closely":[163],"related":[164],"framework":[168,235],"an":[170],"accuracy":[171,218],"86.43%":[173],"90.18%":[175],"segmentation,":[181],"respectively,":[182],"which":[183],"highest":[186],"among":[187],"existing":[188],"methods":[189],"our":[191],"knowledge.":[192],"time":[194],"CTAEM-Net":[197,223],"was":[205,236],"49.72":[206],"\u00b1":[207,211],"9.69s":[208],"120.25":[210],"23.18s":[212],"per":[213],"volume,":[215],"respectively.":[216],"efficiency":[220],"afforded":[221],"will":[224],"make":[225],"possible":[226],"future":[227],"population":[229],"studies.":[230],"generalizability":[232],"also":[237],"demonstrated":[238],"its":[240],"competitive":[241],"performance":[242],"two":[244],"publicly":[245],"available":[246],"datasets":[247],"different":[249],"modalities.":[251]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4210791717","counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":6}],"updated_date":"2025-04-18T03:20:52.663612","created_date":"2022-02-08"}