{"id":"https://openalex.org/W2793504040","doi":"https://doi.org/10.1117/12.2293217","title":"3D GGO candidate extraction in lung CT images using multilevel thresholding on supervoxels","display_name":"3D GGO candidate extraction in lung CT images using multilevel thresholding on supervoxels","publication_year":2018,"publication_date":"2018-02-27","ids":{"openalex":"https://openalex.org/W2793504040","doi":"https://doi.org/10.1117/12.2293217","mag":"2793504040"},"language":"en","primary_location":{"id":"doi:10.1117/12.2293217","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2293217","pdf_url":null,"source":{"id":"https://openalex.org/S4306519508","display_name":"Medical Imaging 2018: 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 2018: 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/A5085061478","display_name":"Xiabi Liu","orcid":"https://orcid.org/0000-0003-1633-0648"},"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":"Xiabi Liu","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/A5101590330","display_name":"Guanghui Han","orcid":"https://orcid.org/0000-0001-9043-722X"},"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":"Guanghui Han","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/A5040595637","display_name":"Xinming Zhao","orcid":"https://orcid.org/0000-0001-7286-771X"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]},{"id":"https://openalex.org/I2801228662","display_name":"Peking Union Medical College Hospital","ror":"https://ror.org/04jztag35","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2801228662"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinming Zhao","raw_affiliation_strings":["Chinese Academy of Medical Sciences (China)","Peking Union Medical College (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Medical Sciences (China)","institution_ids":["https://openalex.org/I200296433"]},{"raw_affiliation_string":"Peking Union Medical College (China)","institution_ids":["https://openalex.org/I2801228662"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050496811","display_name":"Yanfeng Zhao","orcid":"https://orcid.org/0000-0001-6606-9535"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]},{"id":"https://openalex.org/I2801228662","display_name":"Peking Union Medical College Hospital","ror":"https://ror.org/04jztag35","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2801228662"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanfeng Zhao","raw_affiliation_strings":["Chinese Academy of Medical Sciences (China)","Peking Union Medical College (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Medical Sciences (China)","institution_ids":["https://openalex.org/I200296433"]},{"raw_affiliation_string":"Peking Union Medical College (China)","institution_ids":["https://openalex.org/I2801228662"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081603038","display_name":"Chunwu Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]},{"id":"https://openalex.org/I2801228662","display_name":"Peking Union Medical College Hospital","ror":"https://ror.org/04jztag35","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2801228662"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunwu Zhou","raw_affiliation_strings":["Chinese Academy of Medical Sciences (China)","Peking Union Medical College (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Medical Sciences (China)","institution_ids":["https://openalex.org/I200296433"]},{"raw_affiliation_string":"Peking Union Medical College (China)","institution_ids":["https://openalex.org/I2801228662"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102725956","display_name":"Shan Huang","orcid":"https://orcid.org/0000-0002-4926-4109"},"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":"Shan Huang","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"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3668,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63983703,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"12","issue":null,"first_page":"110","last_page":"110"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9958999752998352,"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":0.9958999752998352,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9929999709129333,"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/thresholding","display_name":"Thresholding","score":0.7611572742462158},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6899855136871338},{"id":"https://openalex.org/keywords/ground-glass-opacity","display_name":"Ground-glass opacity","score":0.6052388548851013},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5754997134208679},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46960505843162537},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.4142317771911621},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3829440772533417},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.3282383382320404},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22172701358795166},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1467229425907135},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.09770333766937256}],"concepts":[{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.7611572742462158},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6899855136871338},{"id":"https://openalex.org/C2777001051","wikidata":"https://www.wikidata.org/wiki/Q3150728","display_name":"Ground-glass opacity","level":4,"score":0.6052388548851013},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5754997134208679},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46960505843162537},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.4142317771911621},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3829440772533417},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.3282383382320404},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22172701358795166},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1467229425907135},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.09770333766937256},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C2781182431","wikidata":"https://www.wikidata.org/wiki/Q356033","display_name":"Adenocarcinoma","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2293217","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2293217","pdf_url":null,"source":{"id":"https://openalex.org/S4306519508","display_name":"Medical Imaging 2018: 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 2018: Computer-Aided Diagnosis","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.6600000262260437,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1976027544","https://openalex.org/W1980850407","https://openalex.org/W1987805244","https://openalex.org/W2012355247","https://openalex.org/W2021928864","https://openalex.org/W2053802831","https://openalex.org/W2077750147","https://openalex.org/W2078115938","https://openalex.org/W2079178991","https://openalex.org/W2081178133","https://openalex.org/W2083432437","https://openalex.org/W2091817994","https://openalex.org/W2096553005","https://openalex.org/W2102634410","https://openalex.org/W2111042557","https://openalex.org/W2118246710","https://openalex.org/W2133059825","https://openalex.org/W2152205214","https://openalex.org/W2295850614","https://openalex.org/W2320543574","https://openalex.org/W2409082927","https://openalex.org/W2521468065","https://openalex.org/W2887383290","https://openalex.org/W6670006684","https://openalex.org/W6713859482"],"related_works":["https://openalex.org/W1542224353","https://openalex.org/W138221400","https://openalex.org/W4317671434","https://openalex.org/W2922872563","https://openalex.org/W2549418288","https://openalex.org/W2739092184","https://openalex.org/W2740804836","https://openalex.org/W4321317645","https://openalex.org/W1691631808","https://openalex.org/W1586320973"],"abstract_inverted_index":{"The":[0,121,146],"earlier":[1],"detection":[2,25],"of":[3,9,26,129,162,166],"ground":[4],"glass":[5],"opacity":[6],"(GGO)":[7],"is":[8,28,86,98,112,157],"great":[10],"importance":[11],"since":[12],"GGOs":[13,90,186],"are":[14,70,80],"more":[15],"likely":[16],"to":[17,88,100,117],"be":[18],"malignant":[19],"than":[20],"solid":[21],"nodules.":[22],"However,":[23],"the":[24,59,67,139],"GGO":[27,41,103,119,136,153,172,179],"a":[29,39,127,160],"difficult":[30],"task":[31],"in":[32,51,72],"lung":[33,53,60,131],"cancer":[34],"screening.":[35],"This":[36,84],"paper":[37],"proposes":[38],"novel":[40],"candidate":[42,154],"extraction":[43,155],"method,":[44],"which":[45,69],"performs":[46],"multilevel":[47,109],"thresholding":[48,110],"on":[49,63,114,126],"supervoxels":[50],"3D":[52,73],"CT":[54,132,141],"images.":[55],"Firstly,":[56],"we":[57],"segment":[58],"parenchyma":[61],"based":[62],"Otsu":[64],"algorithm.":[65],"Secondly,":[66],"voxels":[68],"adjacent":[71],"discrete":[74],"space":[75],"and":[76,91,164,177,187],"sharing":[77],"similar":[78],"grayscale":[79],"clustered":[81],"into":[82],"supervoxels.":[83],"procedure":[85],"used":[87,99],"enhance":[89],"reduce":[92],"computational":[93],"complexity.":[94],"Thirdly,":[95],"Hessian":[96],"matrix":[97],"emphasize":[101],"focal":[102,185],"candidates.":[104,120],"Lastly,":[105],"an":[106],"improved":[107],"adaptive":[108],"method":[111,123,156],"applied":[113],"segmented":[115],"clusters":[116],"extract":[118],"proposed":[122,152],"was":[124],"evaluated":[125],"set":[128],"19":[130],"scans":[133],"containing":[134],"166":[135,178],"lesions":[137],"from":[138],"Lung":[140],"Imaging":[142],"Signs":[143],"(LISS)":[144],"database.":[145],"experimental":[147],"results":[148],"show":[149],"that":[150],"our":[151],"effective,":[158],"with":[159],"sensitivity":[161],"100%":[163],"26.3":[165],"false":[167],"positives":[168],"per":[169],"scan":[170],"(665":[171],"candidates,":[173],"499":[174],"non-GGO":[175],"regions":[176],"regions).":[180],"It":[181],"can":[182],"handle":[183],"both":[184],"diffuse":[188],"GGOs.":[189]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}