{"id":"https://openalex.org/W3119260780","doi":"https://doi.org/10.3390/s21020369","title":"Automatic Lung Segmentation on Chest X-rays Using Self-Attention Deep Neural Network","display_name":"Automatic Lung Segmentation on Chest X-rays Using Self-Attention Deep Neural Network","publication_year":2021,"publication_date":"2021-01-07","ids":{"openalex":"https://openalex.org/W3119260780","doi":"https://doi.org/10.3390/s21020369","mag":"3119260780","pmid":"https://pubmed.ncbi.nlm.nih.gov/33430480"},"language":"en","primary_location":{"id":"doi:10.3390/s21020369","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21020369","pdf_url":"https://www.mdpi.com/1424-8220/21/2/369/pdf?version=1610027751","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/21/2/369/pdf?version=1610027751","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100615031","display_name":"Minki Kim","orcid":"https://orcid.org/0000-0002-5587-9935"},"institutions":[{"id":"https://openalex.org/I28615091","display_name":"Kyonggi University","ror":"https://ror.org/032xf8h46","country_code":"KR","type":"education","lineage":["https://openalex.org/I28615091"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minki Kim","raw_affiliation_strings":["School of Computer Science and Engineering, Kyonggi University, Gyeonggi-do 16227, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Kyonggi University, Gyeonggi-do 16227, Korea","institution_ids":["https://openalex.org/I28615091"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051604815","display_name":"Byoung-Dai Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I28615091","display_name":"Kyonggi University","ror":"https://ror.org/032xf8h46","country_code":"KR","type":"education","lineage":["https://openalex.org/I28615091"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Byoung-Dai Lee","raw_affiliation_strings":["School of Computer Science and Engineering, Kyonggi University, Gyeonggi-do 16227, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Kyonggi University, Gyeonggi-do 16227, Korea","institution_ids":["https://openalex.org/I28615091"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5051604815"],"corresponding_institution_ids":["https://openalex.org/I28615091"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":8.7489,"has_fulltext":true,"cited_by_count":76,"citation_normalized_percentile":{"value":0.98388813,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"21","issue":"2","first_page":"369","last_page":"369"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9991000294685364,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9991000294685364,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9988999962806702,"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/segmentation","display_name":"Segmentation","score":0.7706364393234253},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7183636426925659},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6917963027954102},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6715437769889832},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6383979320526123},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.6206380128860474},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5722377300262451},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4904929995536804},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4656446874141693},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.439682275056839},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4254217743873596},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33740177750587463},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1175435483455658},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09449931979179382}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7706364393234253},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7183636426925659},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6917963027954102},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6715437769889832},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6383979320526123},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.6206380128860474},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5722377300262451},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4904929995536804},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4656446874141693},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.439682275056839},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4254217743873596},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33740177750587463},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1175435483455658},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09449931979179382},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008168","descriptor_name":"Lung","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D008168","descriptor_name":"Lung","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D008168","descriptor_name":"Lung","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D014965","descriptor_name":"X-Rays","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014965","descriptor_name":"X-Rays","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014965","descriptor_name":"X-Rays","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":6,"locations":[{"id":"doi:10.3390/s21020369","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21020369","pdf_url":"https://www.mdpi.com/1424-8220/21/2/369/pdf?version=1610027751","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:33430480","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33430480","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":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:750a5029275e4773a613cc9d3cfcacdb","is_oa":true,"landing_page_url":"https://doaj.org/article/750a5029275e4773a613cc9d3cfcacdb","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":"Sensors, Vol 21, Iss 2, p 369 (2021)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:6732878","is_oa":true,"landing_page_url":"http://europepmc.org/pmc/articles/PMC7826788","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:mdpi.com:/1424-8220/21/2/369/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s21020369","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Sensors; Volume 21; Issue 2; Pages: 369","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7826788","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7826788","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":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s21020369","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21020369","pdf_url":"https://www.mdpi.com/1424-8220/21/2/369/pdf?version=1610027751","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321268","display_name":"Kyonggi University","ror":"https://ror.org/032xf8h46"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3119260780.pdf","grobid_xml":"https://content.openalex.org/works/W3119260780.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W1993909515","https://openalex.org/W2194775991","https://openalex.org/W2565639579","https://openalex.org/W2592929672","https://openalex.org/W2743473392","https://openalex.org/W2752782242","https://openalex.org/W2770241596","https://openalex.org/W2771252144","https://openalex.org/W2789440170","https://openalex.org/W2794103425","https://openalex.org/W2798122215","https://openalex.org/W2804488433","https://openalex.org/W2884585870","https://openalex.org/W2902930830","https://openalex.org/W2929617806","https://openalex.org/W2937845726","https://openalex.org/W2949650786","https://openalex.org/W2951559372","https://openalex.org/W2951720371","https://openalex.org/W2955058313","https://openalex.org/W2963351448","https://openalex.org/W2963420686","https://openalex.org/W2981689412","https://openalex.org/W2998175747","https://openalex.org/W3012803970","https://openalex.org/W3034552520","https://openalex.org/W3104809143","https://openalex.org/W6751733626"],"related_works":["https://openalex.org/W3104750253","https://openalex.org/W3021239166","https://openalex.org/W2586273397","https://openalex.org/W2390936256","https://openalex.org/W2016385589","https://openalex.org/W2009559548","https://openalex.org/W2483429559","https://openalex.org/W2890643743","https://openalex.org/W3209312100","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Accurate":[0],"identification":[1],"of":[2,5,26,47,58,76,140,150,179,192,199],"the":[3,22,48,52,56,59,88,93,100,105,111,132,148,151,155,171,183,194],"boundaries":[4],"organs":[6],"or":[7,167],"abnormal":[8],"objects":[9],"(e.g.,":[10],"tumors)":[11],"in":[12,17,21,41,87,154,177,189],"medical":[13,173],"images":[14,121],"is":[15,51],"important":[16],"surgical":[18],"planning":[19],"and":[20,24,61,83,104,128,143,196],"diagnosis":[23],"prognosis":[25],"diseases.":[27],"In":[28],"this":[29],"study,":[30],"we":[31,130],"propose":[32],"a":[33],"deep":[34],"learning-based":[35],"method":[36,50,164],"to":[37,67,81,85,110,136],"segment":[38],"lung":[39,141],"areas":[40,142],"chest":[42],"X-rays.":[43],"The":[44,158],"novel":[45],"aspect":[46],"proposed":[49,133,184],"self-attention":[53],"module,":[54],"where":[55],"outputs":[57],"channel":[60],"spatial":[62],"attention":[63,69,94,134,152,185],"modules":[64,135,153,186],"are":[65,96,108],"combined":[66],"generate":[68],"maps,":[70],"with":[71,99],"each":[72],"highlighting":[73],"those":[74],"regions":[75],"feature":[77,102,113],"maps":[78,95],"that":[79,162],"correspond":[80],"\"what\"":[82],"\"where\"":[84],"attend":[86],"learning":[89],"process,":[90],"respectively.":[91],"Thereafter,":[92],"multiplied":[97],"element-wise":[98],"input":[101,112],"map,":[103],"intermediate":[106],"results":[107,160],"added":[109],"map":[114],"again":[115],"for":[116,126,138],"residual":[117],"learning.":[118],"Using":[119],"X-ray":[120],"collected":[122],"from":[123],"public":[124],"datasets":[125],"training":[127],"evaluation,":[129],"applied":[131],"U-Net":[137],"segmentation":[139,175],"conducted":[144],"experiments":[145],"while":[146],"changing":[147],"locations":[149],"baseline":[156],"network.":[157],"experimental":[159],"showed":[161],"our":[163],"achieved":[165],"comparable":[166],"better":[168],"performance":[169],"than":[170],"existing":[172],"image":[174],"networks":[176],"terms":[178],"Dice":[180],"score":[181],"when":[182],"were":[187],"placed":[188],"lower":[190],"layers":[191],"both":[193],"contracting":[195],"expanding":[197],"paths":[198],"U-Net.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":25},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-12T08:23:45.883708","created_date":"2025-10-10T00:00:00"}
