{"id":"https://openalex.org/W2921344258","doi":"https://doi.org/10.1117/12.2513129","title":"Radiomics analysis on T2-MR image to predict lymphovascular space invasion in cervical cancer","display_name":"Radiomics analysis on T2-MR image to predict lymphovascular space invasion in cervical cancer","publication_year":2019,"publication_date":"2019-03-13","ids":{"openalex":"https://openalex.org/W2921344258","doi":"https://doi.org/10.1117/12.2513129","mag":"2921344258"},"language":"en","primary_location":{"id":"doi:10.1117/12.2513129","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2513129","pdf_url":null,"source":{"id":"https://openalex.org/S4306519510","display_name":"Medical Imaging 2019: Computer-Aided Diagnosis","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2019: Computer-Aided Diagnosis","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/A5100429270","display_name":"Jie Tian","orcid":"https://orcid.org/0000-0003-0498-0432"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Tian","raw_affiliation_strings":["Institute of Automation (China)","Univ. of Chinese Academy of Sciences (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation (China)","institution_ids":["https://openalex.org/I4210094879"]},{"raw_affiliation_string":"Univ. of Chinese Academy of Sciences (China)","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043738311","display_name":"Wang Shou","orcid":"https://orcid.org/0000-0001-9420-719X"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shou Wang","raw_affiliation_strings":["Institute of Automation (China)","Univ. of Chinese Academy of Sciences (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation (China)","institution_ids":["https://openalex.org/I4210094879"]},{"raw_affiliation_string":"Univ. of Chinese Academy of Sciences (China)","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044787086","display_name":"Xi Chen","orcid":"https://orcid.org/0000-0002-5116-7500"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Chen","raw_affiliation_strings":["Beijing Institute of Technology (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology (China)","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030748202","display_name":"Qingxia Wu","orcid":"https://orcid.org/0000-0003-4888-8830"},"institutions":[{"id":"https://openalex.org/I4210133534","display_name":"Henan Provincial People's Hospital","ror":"https://ror.org/03f72zw41","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210133534"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingxia Wu","raw_affiliation_strings":["Henan Provincial People\u2019s Hospital (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan Provincial People\u2019s Hospital (China)","institution_ids":["https://openalex.org/I4210133534"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051776525","display_name":"Yongbei Zhu","orcid":"https://orcid.org/0000-0003-0824-1821"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongbei Zhu","raw_affiliation_strings":["Institute of Automation (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation (China)","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100748037","display_name":"Meiyun Wang","orcid":"https://orcid.org/0000-0003-4454-5005"},"institutions":[{"id":"https://openalex.org/I4210133534","display_name":"Henan Provincial People's Hospital","ror":"https://ror.org/03f72zw41","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210133534"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meiyun Wang","raw_affiliation_strings":["Henan Provincial People's Hospital (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan Provincial People's Hospital (China)","institution_ids":["https://openalex.org/I4210133534"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111822524","display_name":"Zhenyu Liu","orcid":"https://orcid.org/0000-0001-7559-8519"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyu Liu","raw_affiliation_strings":["Institute of Automation (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation (China)","institution_ids":["https://openalex.org/I4210094879"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.02768016,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"144","last_page":"144"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T11885","display_name":"MRI in cancer diagnosis","score":0.9983000159263611,"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/T10668","display_name":"Endometrial and Cervical Cancer Treatments","score":0.9715999960899353,"subfield":{"id":"https://openalex.org/subfields/2729","display_name":"Obstetrics and Gynecology"},"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/radiomics","display_name":"Radiomics","score":0.9182481169700623},{"id":"https://openalex.org/keywords/cervical-cancer","display_name":"Cervical cancer","score":0.6199657320976257},{"id":"https://openalex.org/keywords/lymphovascular-invasion","display_name":"Lymphovascular invasion","score":0.4950358271598816},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49298688769340515},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42252954840660095},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3598596453666687},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.35352998971939087},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3426899015903473},{"id":"https://openalex.org/keywords/metastasis","display_name":"Metastasis","score":0.13824281096458435},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.1291797161102295}],"concepts":[{"id":"https://openalex.org/C2778559731","wikidata":"https://www.wikidata.org/wiki/Q23808793","display_name":"Radiomics","level":2,"score":0.9182481169700623},{"id":"https://openalex.org/C2778220009","wikidata":"https://www.wikidata.org/wiki/Q160105","display_name":"Cervical cancer","level":3,"score":0.6199657320976257},{"id":"https://openalex.org/C2778740770","wikidata":"https://www.wikidata.org/wiki/Q6708283","display_name":"Lymphovascular invasion","level":4,"score":0.4950358271598816},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49298688769340515},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42252954840660095},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3598596453666687},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.35352998971939087},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3426899015903473},{"id":"https://openalex.org/C2779013556","wikidata":"https://www.wikidata.org/wiki/Q181876","display_name":"Metastasis","level":3,"score":0.13824281096458435},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.1291797161102295}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2513129","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2513129","pdf_url":null,"source":{"id":"https://openalex.org/S4306519510","display_name":"Medical Imaging 2019: Computer-Aided Diagnosis","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2019: Computer-Aided Diagnosis","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1980434812","https://openalex.org/W2070789376","https://openalex.org/W2504629029","https://openalex.org/W2732063980","https://openalex.org/W2760796828","https://openalex.org/W2763355946","https://openalex.org/W2765456966","https://openalex.org/W2767128594","https://openalex.org/W2781525129","https://openalex.org/W2899491031","https://openalex.org/W2910380368","https://openalex.org/W4230749240","https://openalex.org/W6633658626","https://openalex.org/W6744207676","https://openalex.org/W6744793224","https://openalex.org/W6755870004","https://openalex.org/W6755984076"],"related_works":["https://openalex.org/W3000891326","https://openalex.org/W4205100762","https://openalex.org/W2734724112","https://openalex.org/W2582997534","https://openalex.org/W3009210156","https://openalex.org/W4388577230","https://openalex.org/W4385221818","https://openalex.org/W3030796519","https://openalex.org/W4383892348","https://openalex.org/W4401336133"],"abstract_inverted_index":{"Lymphovascular":[0],"space":[1],"invasion":[2],"(LVSI)":[3],"is":[4,22,27],"an":[5],"important":[6],"determinant":[7],"for":[8,234],"selecting":[9],"treatment":[10,82],"plan":[11],"in":[12,230],"cervical":[13],"cancer":[14],"(CC).":[15],"For":[16],"CC":[17,87],"patients":[18,88,204],"without":[19],"LVSI,":[20],"conization":[21],"recommended;":[23],"otherwise,":[24],"if":[25],"LVSI":[26,43,69,164,203],"observed,":[28],"hysterectomy":[29],"and":[30,64,92,95,105,127,149,202,219],"pelvic":[31],"lymph":[32],"node":[33],"dissection":[34],"are":[35],"required.":[36],"Despite":[37],"the":[38,113,124,134,167,172,176,182,209,220,231],"importance,":[39],"current":[40],"identification":[41],"of":[42,131,188,192],"can":[44],"only":[45],"be":[46,143],"obtained":[47],"by":[48,70,145,166],"pathological":[49],"examination":[50],"through":[51],"invasive":[52],"biopsy":[53],"or":[54],"after":[55],"surgery.":[56],"In":[57,171],"this":[58],"study,":[59],"we":[60,155,207],"provided":[61],"a":[62,99,106,157],"non-invasive":[63],"preoperative":[65],"method":[66],"to":[67,112,122,142,162],"identify":[68],"radiomics":[71,177,195,210,221],"analysis":[72],"on":[73],"T2-magnetic":[74],"resonance":[75],"image":[76,91,118],"(MRI),":[77],"aiming":[78],"at":[79],"assisting":[80],"personalized":[81],"planning.":[83],"We":[84],"enrolled":[85],"120":[86],"with":[89,212],"T2":[90],"clinical":[93,213,217,227,235],"information,":[94,218],"allocated":[96],"them":[97],"into":[98],"training":[100],"set":[101,108],"(n":[102],"=":[103],"80)":[104],"testing":[107,174],"(n=":[109],"40)":[110],"according":[111],"diagnostic":[114],"time.":[115],"Afterwards,":[116],"839":[117,135],"features":[119,139],"were":[120,140],"extracted":[121],"reflect":[123],"intensity,":[125],"shape,":[126],"high-dimensional":[128],"texture":[129],"information":[130],"CC.":[132],"Among":[133],"radiomic":[136,169],"features,":[137],"3":[138,168],"identified":[141],"discriminative":[144],"Least":[146],"absolute":[147],"shrinkage":[148],"selection":[150],"operator":[151],"(Lasso)-Logistic":[152],"regression.":[153],"Finally,":[154],"built":[156],"support":[158],"vector":[159],"machine":[160],"(SVM)":[161],"predict":[163],"status":[165],"features.":[170],"independent":[173],"set,":[175],"model":[178,211,214,222],"achieved":[179],"area":[180],"under":[181],"receiver":[183],"operating":[184],"characteristic":[185],"curve":[186],"(AUC)":[187],"0.7356,":[189],"classification":[190],"accuracy":[191],"0.7287.":[193],"The":[194],"signature":[196],"showed":[197,223],"significant":[198,224],"difference":[199],"between":[200],"non-LVSI":[201],"(p<0.05).":[205],"Furthermore,":[206],"compared":[208],"that":[215],"uses":[216],"improvement":[225],"than":[226],"factors":[228],"(AUC=0.5967":[229],"validation":[232],"cohort":[233],"model).":[236]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}