{"id":"https://openalex.org/W2791373118","doi":"https://doi.org/10.1117/12.2293114","title":"Automatic segmentation of thoracic aorta segments in low-dose chest CT","display_name":"Automatic segmentation of thoracic aorta segments in low-dose chest CT","publication_year":2018,"publication_date":"2018-03-02","ids":{"openalex":"https://openalex.org/W2791373118","doi":"https://doi.org/10.1117/12.2293114","mag":"2791373118"},"language":"en","primary_location":{"id":"doi:10.1117/12.2293114","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2293114","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2018: Image Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1810.05727","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080550301","display_name":"Julia M. H. Noothout","orcid":"https://orcid.org/0000-0001-6013-5896"},"institutions":[{"id":"https://openalex.org/I3018483916","display_name":"University Medical Center Utrecht","ror":"https://ror.org/0575yy874","country_code":"NL","type":"funder","lineage":["https://openalex.org/I3018483916"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Julia Noothout","raw_affiliation_strings":["Univ. Medical Ctr. Utrecht (Netherlands)"],"affiliations":[{"raw_affiliation_string":"Univ. Medical Ctr. Utrecht (Netherlands)","institution_ids":["https://openalex.org/I3018483916"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018266214","display_name":"Bob D. de Vos","orcid":"https://orcid.org/0000-0002-8358-6849"},"institutions":[{"id":"https://openalex.org/I3018483916","display_name":"University Medical Center Utrecht","ror":"https://ror.org/0575yy874","country_code":"NL","type":"funder","lineage":["https://openalex.org/I3018483916"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Bob de Vos","raw_affiliation_strings":["Univ. Medical Ctr. Utrecht (Netherlands)"],"affiliations":[{"raw_affiliation_string":"Univ. Medical Ctr. Utrecht (Netherlands)","institution_ids":["https://openalex.org/I3018483916"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028639654","display_name":"Jelmer M. Wolterink","orcid":"https://orcid.org/0000-0001-5505-475X"},"institutions":[{"id":"https://openalex.org/I3018483916","display_name":"University Medical Center Utrecht","ror":"https://ror.org/0575yy874","country_code":"NL","type":"funder","lineage":["https://openalex.org/I3018483916"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Jelmer Wolterink","raw_affiliation_strings":["Univ. Medical Ctr. Utrecht (Netherlands)"],"affiliations":[{"raw_affiliation_string":"Univ. Medical Ctr. Utrecht (Netherlands)","institution_ids":["https://openalex.org/I3018483916"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084070018","display_name":"Ivana I\u0161gum","orcid":"https://orcid.org/0000-0003-1869-5034"},"institutions":[{"id":"https://openalex.org/I3018483916","display_name":"University Medical Center Utrecht","ror":"https://ror.org/0575yy874","country_code":"NL","type":"funder","lineage":["https://openalex.org/I3018483916"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Ivana Isgum","raw_affiliation_strings":["Univ. Medical Ctr. Utrecht (Netherlands)"],"affiliations":[{"raw_affiliation_string":"Univ. Medical Ctr. Utrecht (Netherlands)","institution_ids":["https://openalex.org/I3018483916"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5080550301"],"corresponding_institution_ids":["https://openalex.org/I3018483916"],"apc_list":null,"apc_paid":null,"fwci":1.9962,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.85586357,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"63","last_page":"63"},"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":0.9988999962806702,"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":0.9988999962806702,"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/T10372","display_name":"Cardiac Imaging and Diagnostics","score":0.9980999827384949,"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":0.9948999881744385,"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/thoracic-aorta","display_name":"Thoracic aorta","score":0.551113486289978},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.535344660282135},{"id":"https://openalex.org/keywords/aorta","display_name":"Aorta","score":0.4927056133747101},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46170738339424133},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.4215441346168518},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.40010666847229004},{"id":"https://openalex.org/keywords/nuclear-medicine","display_name":"Nuclear medicine","score":0.34684091806411743},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31634414196014404},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.18000924587249756}],"concepts":[{"id":"https://openalex.org/C2776864027","wikidata":"https://www.wikidata.org/wiki/Q615993","display_name":"Thoracic aorta","level":3,"score":0.551113486289978},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.535344660282135},{"id":"https://openalex.org/C2779980429","wikidata":"https://www.wikidata.org/wiki/Q101004","display_name":"Aorta","level":2,"score":0.4927056133747101},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46170738339424133},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.4215441346168518},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.40010666847229004},{"id":"https://openalex.org/C2989005","wikidata":"https://www.wikidata.org/wiki/Q214963","display_name":"Nuclear medicine","level":1,"score":0.34684091806411743},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31634414196014404},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.18000924587249756}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1117/12.2293114","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2293114","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2018: Image Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1810.05727","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1810.05727","pdf_url":"https://arxiv.org/pdf/1810.05727","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:amcpub:oai:pure.amc.nl:publications/5cdeb0ca-d2fd-43f2-802d-5bcbfe2038e1","is_oa":false,"landing_page_url":"https://pure.amc.nl/en/publications/automatic-segmentation-of-thoracic-aorta-segments-in-lowdose-chest-ct(5cdeb0ca-d2fd-43f2-802d-5bcbfe2038e1).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Medical Imaging 2018: Image Processing, 10574","raw_type":"info:eu-repo/semantics/conferencepaper"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1810.05727","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1810.05727","pdf_url":"https://arxiv.org/pdf/1810.05727","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1213336605","https://openalex.org/W1522301498","https://openalex.org/W1836465849","https://openalex.org/W2011214625","https://openalex.org/W2052971463","https://openalex.org/W2095705004","https://openalex.org/W2117430606","https://openalex.org/W2162140684","https://openalex.org/W2432481613","https://openalex.org/W2575226059","https://openalex.org/W2590651460","https://openalex.org/W2949117887","https://openalex.org/W2962914239","https://openalex.org/W2963840672","https://openalex.org/W2964121744","https://openalex.org/W3102109558","https://openalex.org/W4253285246","https://openalex.org/W6631190155","https://openalex.org/W6638667902","https://openalex.org/W6653483111","https://openalex.org/W6674330103","https://openalex.org/W6696085341","https://openalex.org/W6718240422","https://openalex.org/W6731742386"],"related_works":["https://openalex.org/W2361751875","https://openalex.org/W2057075445","https://openalex.org/W2376591618","https://openalex.org/W2170979704","https://openalex.org/W2025577687","https://openalex.org/W1913532336","https://openalex.org/W3210247111","https://openalex.org/W1483752266","https://openalex.org/W2399617289","https://openalex.org/W1965165924"],"abstract_inverted_index":{"Morphological":[0],"analysis":[1],"and":[2,14,23,32,51,88,108,135,151,155,168,182,206],"identification":[3],"of":[4,77,100,144,161,204,208],"pathologies":[5],"in":[6,17,25,56,85,197],"the":[7,45,48,52,97,101,114,117,133,140,176,179,183,191,201,209],"aorta":[8,55],"are":[9],"important":[10],"for":[11,175],"cardiovascular":[12],"diagnosis":[13],"risk":[15],"assessment":[16],"patients.":[18],"Manual":[19],"annotation":[20],"is":[21],"time-consuming":[22],"cumbersome":[24],"CT":[26,59],"scans":[27,128],"acquired":[28],"without":[29,60],"contrast":[30,61],"enhancement":[31],"with":[33,73,116],"low":[34],"radiation":[35],"dose.":[36],"Hence,":[37],"we":[38],"propose":[39],"an":[40],"automatic":[41],"method":[42,193],"to":[43,113,131,138],"segment":[44],"ascending":[46,177],"aorta,":[47,178,185],"aortic":[49,180],"arch":[50,181],"thoracic":[53,210],"descending":[54,184],"low-dose":[57],"chest":[58],"enhancement.":[62],"Segmentation":[63],"was":[64],"performed":[65,125],"using":[66],"a":[67,74,94],"dilated":[68],"convolutional":[69],"neural":[70],"network":[71,134],"(CNN),":[72],"receptive":[75],"field":[76],"131":[78,80],"\u00d7":[79],"voxels,":[81],"that":[82,190],"classified":[83],"voxels":[84,109],"axial,":[86],"coronal":[87],"sagittal":[89],"image":[90],"slices.":[91],"To":[92],"obtain":[93],"final":[95],"segmentation,":[96],"obtained":[98,174],"probabilities":[99],"three":[102],"planes":[103],"were":[104,110,124,129,173],"averaged":[105],"per":[106],"class,":[107],"subsequently":[111],"assigned":[112],"class":[115,119],"highest":[118],"probability.":[120],"Two-fold":[121],"cross-validation":[122],"experiments":[123],"where":[126],"ten":[127,137],"used":[130,196],"train":[132],"another":[136],"evaluate":[139],"performance.":[141],"Dice":[142],"coefficients":[143],"0.83":[145],"±":[146,149,153,163,166,170],"0.07,":[147],"0.86":[148],"0.06":[150],"0.88":[152],"0.05,":[154],"Average":[156],"Symmetrical":[157],"Surface":[158],"Distances":[159],"(ASSDs)":[160],"2.44":[162],"1.28,":[164],"1.56":[165],"0.68":[167],"1.87":[169],"1.30":[171],"mm":[172],"respectively.":[186],"The":[187],"results":[188],"indicate":[189],"proposed":[192],"could":[194],"be":[195],"large-scale":[198],"studies":[199],"analyzing":[200],"anatomical":[202],"location":[203],"pathology":[205],"morphology":[207],"aorta.":[211]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}