乐胖代购免代理版

{"id":"https://openalex.org/W2592431845","doi":"https://doi.org/10.1117/12.2250360","title":"Applying a deep learning based CAD scheme to segment and quantify visceral and subcutaneous fat areas from CT images","display_name":"Applying a deep learning based CAD scheme to segment and quantify visceral and subcutaneous fat areas from CT images","publication_year":2017,"publication_date":"2017-03-03","ids":{"openalex":"https://openalex.org/W2592431845","doi":"https://doi.org/10.1117/12.2250360","mag":"2592431845"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2250360","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5101572876","display_name":"Yunzhi Wang","orcid":"https://orcid.org/0000-0001-9033-3156"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yunzhi Wang","raw_affiliation_strings":["Univ. of Oklahoma (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Oklahoma (United States)","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108101897","display_name":"Yuchen Qiu","orcid":null},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuchen Qiu","raw_affiliation_strings":["Univ. of Oklahoma (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Oklahoma (United States)","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113128567","display_name":"Theresa Thai","orcid":null},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Theresa Thai","raw_affiliation_strings":["Health Science Ctr. of Univ. of Oklahoma (United States)"],"affiliations":[{"raw_affiliation_string":"Health Science Ctr. of Univ. of Oklahoma (United States)","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069337573","display_name":"Kathleen N. Moore","orcid":"https://orcid.org/0000-0002-5803-0718"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kathleen Moore","raw_affiliation_strings":["Health Science Ctr. of Univ. of Oklahoma (United States)"],"affiliations":[{"raw_affiliation_string":"Health Science Ctr. of Univ. of Oklahoma (United States)","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100410286","display_name":"Hong Liu","orcid":"https://orcid.org/0000-0002-0896-8409"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hong Liu","raw_affiliation_strings":["Univ. of Oklahoma (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Oklahoma (United States)","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045998635","display_name":"Bin Zheng","orcid":"https://orcid.org/0000-0002-7682-6648"},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bin Zheng","raw_affiliation_strings":["Univ. of Oklahoma (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Oklahoma (United States)","institution_ids":["https://openalex.org/I8692664"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.204,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":4,"citation_normalized_percentile":{"value":0.739325,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":77,"max":79},"biblio":{"volume":"10134","issue":null,"first_page":"101343G","last_page":"101343G"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T12979","display_name":"Cardiovascular Disease and Adiposity","score":0.993,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular 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/T12979","display_name":"Cardiovascular Disease and Adiposity","score":0.993,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular 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/T10528","display_name":"Adipokines, Inflammation, and Metabolic Diseases","score":0.9093,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/T12173","display_name":"Body Contouring and Surgery","score":0.9052,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/computer-aided-diagnosis","display_name":"Computer-Aided Diagnosis","score":0.559192}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7323756},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7298052},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.70580757},{"id":"https://openalex.org/C194789388","wikidata":"https://www.wikidata.org/wiki/Q17855283","display_name":"CAD","level":2,"score":0.6841179},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.65976083},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5947223},{"id":"https://openalex.org/C2779549770","wikidata":"https://www.wikidata.org/wiki/Q1122413","display_name":"Computer-aided diagnosis","level":2,"score":0.559192},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.55235296},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5233975},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4848186},{"id":"https://openalex.org/C2779983558","wikidata":"https://www.wikidata.org/wiki/Q9597","display_name":"Abdomen","level":2,"score":0.44753906},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.41743845},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.28654987},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.24143821},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15023798},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.06941441},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2250360","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.68}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":23,"referenced_works":["https://openalex.org/W1966847100","https://openalex.org/W1980968791","https://openalex.org/W2032677261","https://openalex.org/W2106690226","https://openalex.org/W2112796928","https://openalex.org/W2144354855","https://openalex.org/W2160921359","https://openalex.org/W2165047605","https://openalex.org/W2220907510","https://openalex.org/W2295384772","https://openalex.org/W2296661647","https://openalex.org/W2304433118","https://openalex.org/W2317417577","https://openalex.org/W2338271170","https://openalex.org/W2339824777","https://openalex.org/W2342295631","https://openalex.org/W2344858100","https://openalex.org/W2418815986","https://openalex.org/W2508159727","https://openalex.org/W2518247117","https://openalex.org/W2963673193","https://openalex.org/W317170363","https://openalex.org/W4231109964"],"related_works":["https://openalex.org/W615772105","https://openalex.org/W4229543669","https://openalex.org/W2999505641","https://openalex.org/W2945629533","https://openalex.org/W2401866201","https://openalex.org/W2013631688","https://openalex.org/W1978794434","https://openalex.org/W1783185948","https://openalex.org/W1589419489","https://openalex.org/W1554029525"],"abstract_inverted_index":{"Abdominal":[0],"obesity":[1],"is":[2,35],"strongly":[3],"associated":[4],"with":[5,213,217],"a":[6,20,40],"number":[7],"of":[8,13,15,32,95,151,164,176,190],"diseases":[9],"and":[10,28,38,58,78,87,104,122,205,208],"accurately":[11],"assessment":[12],"subtypes":[14],"adipose":[16],"tissue":[17],"volume":[18],"plays":[19],"significant":[21],"role":[22],"in":[23],"predicting":[24],"disease":[25],"risk,":[26],"diagnosis":[27],"prognosis.":[29],"The":[30,90],"objective":[31],"this":[33,185],"study":[34,186],"to":[36,51,113,119,130,135,147,157,197],"develop":[37],"evaluate":[39,148],"new":[41,91],"computer-aided":[42],"detection":[43],"(CAD)":[44],"scheme":[45,93,196],"based":[46,194],"on":[47,64],"deep":[48,192],"learning":[49,193],"models":[50],"automatically":[52,114],"segment":[53,206],"subcutaneous":[54],"fat":[55,61,177],"areas":[56,62,121],"(SFA)":[57],"visceral":[59],"(VFA)":[60],"depicting":[63],"CT":[65,70,111,116,165,203,211],"images.":[66],"A":[67],"dataset":[68],"involving":[69],"images":[71],"from":[72,141,202,210],"40":[73],"patients":[74],"were":[75],"retrospectively":[76],"collected":[77],"equally":[79],"divided":[80],"into":[81],"two":[82,96],"independent":[83],"groups":[84],"(i.e.":[85],"training":[86],"testing":[88,143],"group).":[89],"CAD":[92,154,195],"consisted":[94],"sequential":[97],"convolutional":[98],"neural":[99],"networks":[100],"(CNNs)":[101],"namely,":[102],"Selection-CNN":[103,106,170],"Segmentation-CNN.":[105],"was":[107,124,145],"trained":[108,125],"using":[109,126,180,191],"2,240":[110],"slices":[112,117,166,212],"select":[115],"belonging":[118,134],"abdomen":[120],"SegmentationCNN":[123],"84,000":[127],"fat-pixel":[128],"patches":[129],"classify":[131],"fat-pixels":[132],"as":[133],"SFA":[136,207],"or":[137],"VFA.":[138],"Then,":[139],"data":[140],"the":[142,149,152,161,174,188],"group":[144],"used":[146],"performance":[150],"optimized":[153],"scheme.":[155],"Comparing":[156],"manually":[158],"labelled":[159],"results,":[160],"classification":[162],"accuracy":[163,175],"selection":[167],"generated":[168],"by":[169],"yielded":[171,182],"95.8%,":[172],"while":[173],"pixel":[178],"segmentation":[179,219],"Segmentation-CNN":[181],"96.8%.":[183],"Therefore,":[184],"demonstrated":[187],"feasibility":[189],"recognize":[198],"human":[199],"abdominal":[200],"section":[201],"scans":[204],"VFA":[209],"high":[214],"agreement":[215],"compared":[216],"subjective":[218],"results.":[220]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2592431845","counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2024-12-17T01:08:05.911256","created_date":"2017-03-16"}