{"id":"https://openalex.org/W3046355568","doi":"https://doi.org/10.1109/isbiworkshops50223.2020.9153455","title":"Lung Lobe Segmentation With Automated Quality Assurance Using Deep Convolutional Neural Networks","display_name":"Lung Lobe Segmentation With Automated Quality Assurance Using Deep Convolutional Neural Networks","publication_year":2020,"publication_date":"2020-04-01","ids":{"openalex":"https://openalex.org/W3046355568","doi":"https://doi.org/10.1109/isbiworkshops50223.2020.9153455","mag":"3046355568"},"language":"en","primary_location":{"id":"doi:10.1109/isbiworkshops50223.2020.9153455","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbiworkshops50223.2020.9153455","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 17th International Symposium on Biomedical Imaging Workshops (ISBI Workshops)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5038840367","display_name":"Sundaresh Ram","orcid":"https://orcid.org/0000-0003-1828-9722"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sundaresh Ram","raw_affiliation_strings":["Department of Radiology, University of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076234168","display_name":"Stephen M. Humphries","orcid":"https://orcid.org/0000-0002-5113-4530"},"institutions":[{"id":"https://openalex.org/I3019586173","display_name":"National Jewish Health","ror":"https://ror.org/016z2bp30","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I3019586173"]},{"id":"https://openalex.org/I921990950","display_name":"University of Colorado Denver","ror":"https://ror.org/02hh7en24","country_code":"US","type":"education","lineage":["https://openalex.org/I921990950"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stephen M. Humphries","raw_affiliation_strings":["National Jewish Health, Denver, CO, USA"],"affiliations":[{"raw_affiliation_string":"National Jewish Health, Denver, CO, USA","institution_ids":["https://openalex.org/I3019586173","https://openalex.org/I921990950"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023897162","display_name":"David A. Lynch","orcid":"https://orcid.org/0000-0002-6329-2325"},"institutions":[{"id":"https://openalex.org/I921990950","display_name":"University of Colorado Denver","ror":"https://ror.org/02hh7en24","country_code":"US","type":"education","lineage":["https://openalex.org/I921990950"]},{"id":"https://openalex.org/I3019586173","display_name":"National Jewish Health","ror":"https://ror.org/016z2bp30","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I3019586173"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David A. Lynch","raw_affiliation_strings":["National Jewish Health, Denver, CO, USA"],"affiliations":[{"raw_affiliation_string":"National Jewish Health, Denver, CO, USA","institution_ids":["https://openalex.org/I3019586173","https://openalex.org/I921990950"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070937580","display_name":"Craig J. Galb\u00e1n","orcid":"https://orcid.org/0000-0001-5596-7487"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Craig J. Galban","raw_affiliation_strings":["Department of Radiology, University of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060236564","display_name":"Charles R. Hatt","orcid":"https://orcid.org/0000-0001-7097-5434"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Charles R. Hatt","raw_affiliation_strings":["Department of Radiology, University of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5038840367"],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":0.3304,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.62792156,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9973000288009644,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9973000288009644,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9970999956130981,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9943000078201294,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8255109190940857},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7999252080917358},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7960332632064819},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7530224323272705},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.560836911201477},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5533011555671692},{"id":"https://openalex.org/keywords/quality-assurance","display_name":"Quality assurance","score":0.5518980622291565},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5170686841011047},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49880456924438477},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.4452746510505676},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4222245216369629},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38863661885261536},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38302159309387207},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.24242308735847473},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.07542568445205688}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8255109190940857},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7999252080917358},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7960332632064819},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7530224323272705},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.560836911201477},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5533011555671692},{"id":"https://openalex.org/C106436119","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assurance","level":3,"score":0.5518980622291565},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5170686841011047},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49880456924438477},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4452746510505676},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4222245216369629},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38863661885261536},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38302159309387207},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.24242308735847473},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.07542568445205688},{"id":"https://openalex.org/C2778618615","wikidata":"https://www.wikidata.org/wiki/Q4008393","display_name":"External quality assessment","level":2,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbiworkshops50223.2020.9153455","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbiworkshops50223.2020.9153455","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 17th International Symposium on Biomedical Imaging Workshops (ISBI Workshops)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W155524655","https://openalex.org/W582134693","https://openalex.org/W1812394418","https://openalex.org/W1901129140","https://openalex.org/W2082907106","https://openalex.org/W2149799076","https://openalex.org/W2346062110","https://openalex.org/W2592929672","https://openalex.org/W2600383743","https://openalex.org/W2887976372","https://openalex.org/W2899771611","https://openalex.org/W2963238274","https://openalex.org/W2964059111","https://openalex.org/W6617145748","https://openalex.org/W6639824700","https://openalex.org/W6730042731","https://openalex.org/W6735443497","https://openalex.org/W6756040250"],"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/W2197494698","https://openalex.org/W3024479225","https://openalex.org/W4323287533","https://openalex.org/W3171371563"],"abstract_inverted_index":{"Despite":[0],"good":[1],"performance":[2],"for":[3,60,75],"medical":[4],"image":[5],"segmentation,":[6],"deep":[7,76],"convolutional":[8],"neural":[9],"networks":[10],"(CNNs)":[11],"have":[12],"not":[13,35],"been":[14],"widely":[15],"accepted":[16],"in":[17,31,49,81],"clinical":[18],"practice":[19],"as":[20,54],"they":[21],"are":[22,34],"complex":[23],"and":[24,41,109,117,138],"tend":[25],"to":[26,43,135],"fail":[27],"silently.":[28],"Additionally,":[29],"uncertainty":[30,74,92,100,130],"their":[32],"predictions":[33,51],"well":[36],"understood,":[37],"making":[38],"them":[39],"obscure":[40],"challenging":[42],"interpret.":[44],"Automatically":[45],"detecting":[46],"possible":[47],"failures":[48],"network":[50],"is":[52,115,132],"important,":[53],"we":[55,71,97],"can":[56,106],"refer":[57],"such":[58,128],"cases":[59],"manual":[61],"inspection":[62],"or":[63],"correction":[64],"by":[65,86],"human":[66],"observers.":[67],"In":[68],"this":[69,95],"paper,":[70],"analyse":[72],"the":[73,119],"CNN-based":[77],"lung":[78],"lobe":[79],"segmentation":[80,136,145],"computed":[82],"tomography":[83],"(CT)":[84],"scans":[85],"proposing":[87],"a":[88,104,111],"test-time":[89],"augmentation-based":[90],"aleatoric":[91],"measure.":[93],"Through":[94],"analysis,":[96],"produce":[98],"spatial":[99],"maps,":[101],"from":[102],"which":[103],"clinician":[105],"observe":[107],"where":[108],"why":[110],"system":[112],"thinks":[113],"it":[114],"failing,":[116],"quantify":[118],"image-level":[120],"prediction":[121],"of":[122,144],"failure.":[123],"Our":[124],"results":[125],"show":[126],"that":[127],"an":[129,141],"measure":[131,143],"highly":[133],"correlated":[134],"accuracy":[137],"therefore":[139],"presents":[140],"inherent":[142],"quality.":[146]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}