{"id":"https://openalex.org/W3087915906","doi":"https://doi.org/10.1109/access.2020.3026168","title":"Pulmonary Nodule Detection Using V-Net and High-Level Descriptor Based SVM Classifier","display_name":"Pulmonary Nodule Detection Using V-Net and High-Level Descriptor Based SVM Classifier","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3087915906","doi":"https://doi.org/10.1109/access.2020.3026168","mag":"3087915906"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3026168","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3026168","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09204700.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/ielx7/6287639/8948470/09204700.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021079197","display_name":"Yuyun Ye","orcid":"https://orcid.org/0000-0003-3395-2174"},"institutions":[{"id":"https://openalex.org/I87208437","display_name":"University of Tulsa","ror":"https://ror.org/04wn28048","country_code":"US","type":"education","lineage":["https://openalex.org/I87208437"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yuyun Ye","raw_affiliation_strings":["The University of Tulsa, Tulsa, OK, USA"],"affiliations":[{"raw_affiliation_string":"The University of Tulsa, Tulsa, OK, USA","institution_ids":["https://openalex.org/I87208437"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013068815","display_name":"Miao Tian","orcid":"https://orcid.org/0000-0002-1155-3220"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Miao Tian","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101717096","display_name":"Qiyu Liu","orcid":"https://orcid.org/0000-0003-0924-4514"},"institutions":[{"id":"https://openalex.org/I4210095398","display_name":"Mianyang Central Hospital","ror":"https://ror.org/00s528j33","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210095398"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiyu Liu","raw_affiliation_strings":["Mianyang Central Hospital, Mianyang, China"],"affiliations":[{"raw_affiliation_string":"Mianyang Central Hospital, Mianyang, China","institution_ids":["https://openalex.org/I4210095398"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013178600","display_name":"Heng\u2010Ming Tai","orcid":"https://orcid.org/0000-0002-0162-7492"},"institutions":[{"id":"https://openalex.org/I87208437","display_name":"University of Tulsa","ror":"https://ror.org/04wn28048","country_code":"US","type":"education","lineage":["https://openalex.org/I87208437"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Heng-Ming Tai","raw_affiliation_strings":["The University of Tulsa, Tulsa, OK, USA"],"affiliations":[{"raw_affiliation_string":"The University of Tulsa, Tulsa, OK, USA","institution_ids":["https://openalex.org/I87208437"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5021079197"],"corresponding_institution_ids":["https://openalex.org/I87208437"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.016,"has_fulltext":true,"cited_by_count":26,"citation_normalized_percentile":{"value":0.89518523,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"176033","last_page":"176041"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9975000023841858,"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"}},"topics":[{"id":"https://openalex.org/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9975000023841858,"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"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9697999954223633,"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":0.9607999920845032,"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/support-vector-machine","display_name":"Support vector machine","score":0.8548024892807007},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7378075122833252},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6833243370056152},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6635816693305969},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6357579231262207},{"id":"https://openalex.org/keywords/cad","display_name":"CAD","score":0.5949201583862305},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0707036554813385}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8548024892807007},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7378075122833252},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6833243370056152},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6635816693305969},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6357579231262207},{"id":"https://openalex.org/C194789388","wikidata":"https://www.wikidata.org/wiki/Q17855283","display_name":"CAD","level":2,"score":0.5949201583862305},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0707036554813385},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3026168","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3026168","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09204700.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:e78f1ebad1a048369a56ede36fb35153","is_oa":true,"landing_page_url":"https://doaj.org/article/e78f1ebad1a048369a56ede36fb35153","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 176033-176041 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3026168","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3026168","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09204700.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":[{"score":0.8399999737739563,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3087915906.pdf","grobid_xml":"https://content.openalex.org/works/W3087915906.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1901129140","https://openalex.org/W1968009201","https://openalex.org/W1986649315","https://openalex.org/W1997499435","https://openalex.org/W2039051707","https://openalex.org/W2078014989","https://openalex.org/W2159498975","https://openalex.org/W2159543062","https://openalex.org/W2161969291","https://openalex.org/W2170552969","https://openalex.org/W2322371438","https://openalex.org/W2464708700","https://openalex.org/W2524399695","https://openalex.org/W2584017349","https://openalex.org/W2613475099","https://openalex.org/W2613718673","https://openalex.org/W2734776202","https://openalex.org/W2766353760","https://openalex.org/W2781660331","https://openalex.org/W2801761532","https://openalex.org/W2802087177","https://openalex.org/W2806695489","https://openalex.org/W2887808321","https://openalex.org/W2899136361","https://openalex.org/W2899912692","https://openalex.org/W2910047409","https://openalex.org/W2917412692","https://openalex.org/W2923991973","https://openalex.org/W2924414193","https://openalex.org/W2937068764","https://openalex.org/W2947415482","https://openalex.org/W2949754230","https://openalex.org/W2950800384","https://openalex.org/W2956679869","https://openalex.org/W2962852641","https://openalex.org/W2962914239","https://openalex.org/W2997315966","https://openalex.org/W3007997946","https://openalex.org/W3028412523","https://openalex.org/W3102190365","https://openalex.org/W6620707391","https://openalex.org/W6639824700","https://openalex.org/W6683344514","https://openalex.org/W6714138976"],"related_works":["https://openalex.org/W2345184372","https://openalex.org/W3013515612","https://openalex.org/W2136184105","https://openalex.org/W2187500075","https://openalex.org/W2041399278","https://openalex.org/W2160451891","https://openalex.org/W2336974148","https://openalex.org/W2056016498","https://openalex.org/W2389470892","https://openalex.org/W4293087713"],"abstract_inverted_index":{"Early":[0],"detection":[1,27,44,66],"of":[2,14,99,127],"the":[3,10,47,68,86,118,125,128],"pulmonary":[4,42],"nodule":[5,26,43,64],"is":[6,62,70,82],"critical":[7,97],"to":[8,28,84,123],"increase":[9],"five-year":[11],"survival":[12],"rate":[13],"lung":[15],"cancer.":[16],"Many":[17],"computer-aided":[18],"diagnosis":[19],"(CAD)":[20],"systems":[21],"have":[22],"been":[23],"proposed":[24,91,129],"for":[25,63,71,80],"assist":[29],"radiologists":[30],"in":[31,104],"diagnosis.":[32],"Along":[33],"this":[34,36],"direction,":[35],"paper":[37],"proposes":[38],"a":[39,51],"novel":[40],"automated":[41],"model":[45],"using":[46,117],"modified":[48],"V-Nets":[49],"and":[50,67,112],"high-level":[52],"descriptor":[53],"based":[54,110],"support":[55],"vector":[56],"machine":[57],"(SVM)":[58],"classifier.":[59],"The":[60,90],"former":[61],"candidate":[65],"latter":[69],"false":[72],"positive":[73],"(FP)":[74],"reduction.":[75],"A":[76],"hard":[77],"mining":[78],"scheme":[79],"retraining":[81],"devised":[83],"improve":[85],"FP":[87,105],"reduction":[88,106],"performance.":[89],"SVM":[92,109],"classifier,":[93],"which":[94],"employs":[95],"more":[96],"features":[98],"CT":[100],"images,":[101],"performs":[102],"superior":[103],"than":[107],"other":[108],"classifiers":[111],"CNN":[113],"classifiers.":[114],"Experimental":[115],"results":[116],"LIDC-IDRI":[119],"dataset":[120],"are":[121],"presented":[122],"demonstrate":[124],"effectiveness":[126],"CAD":[130],"model.":[131]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
