{"id":"https://openalex.org/W2205795857","doi":"https://doi.org/10.1109/tmi.2015.2474119","title":"Lung Lesion Extraction Using a Toboggan Based Growing Automatic Segmentation Approach","display_name":"Lung Lesion Extraction Using a Toboggan Based Growing Automatic Segmentation Approach","publication_year":2015,"publication_date":"2015-08-27","ids":{"openalex":"https://openalex.org/W2205795857","doi":"https://doi.org/10.1109/tmi.2015.2474119","mag":"2205795857","pmid":"https://pubmed.ncbi.nlm.nih.gov/26336121"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2015.2474119","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2015.2474119","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5077642129","display_name":"Jiangdian Song","orcid":"https://orcid.org/0000-0002-3355-9930"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangdian Song","raw_affiliation_strings":["Chinese Academy of Sciences, Institute of Automation, Beijing, China","Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Institute of Automation, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102973288","display_name":"Caiyun Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Caiyun Yang","raw_affiliation_strings":["Chinese Academy of Sciences, Institute of Automation, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Institute of Automation, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004583777","display_name":"Li Fan","orcid":"https://orcid.org/0000-0003-4722-3933"},"institutions":[{"id":"https://openalex.org/I177933477","display_name":"Second Military Medical University","ror":"https://ror.org/04tavpn47","country_code":"CN","type":"education","lineage":["https://openalex.org/I177933477"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Fan","raw_affiliation_strings":["Department of Radiology, Changzheng Hospital, Second Military Medical University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Changzheng Hospital, Second Military Medical University, Shanghai, China","institution_ids":["https://openalex.org/I177933477"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100366717","display_name":"Kun Wang","orcid":"https://orcid.org/0000-0003-2513-768X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Wang","raw_affiliation_strings":["Chinese Academy of Sciences, Institute of Automation, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Institute of Automation, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063417182","display_name":"Feng Yang","orcid":"https://orcid.org/0000-0002-8334-7450"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Yang","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100327225","display_name":"Shiyuan Liu","orcid":"https://orcid.org/0000-0002-0266-4666"},"institutions":[{"id":"https://openalex.org/I177933477","display_name":"Second Military Medical University","ror":"https://ror.org/04tavpn47","country_code":"CN","type":"education","lineage":["https://openalex.org/I177933477"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiyuan Liu","raw_affiliation_strings":["Department of Radiology, Changzheng Hospital, Second Military Medical University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Changzheng Hospital, Second Military Medical University, Shanghai, China","institution_ids":["https://openalex.org/I177933477"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112284258","display_name":"Jie Tian","orcid":"https://orcid.org/0009-0001-7785-849X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Tian","raw_affiliation_strings":["Chinese Academy of Sciences, Institute of Automation, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Institute of Automation, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.7689,"has_fulltext":false,"cited_by_count":101,"citation_normalized_percentile":{"value":0.97784954,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"35","issue":"1","first_page":"337","last_page":"353"},"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":0.9988999962806702,"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"}},"topics":[{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","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":0.9987999796867371,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9891999959945679,"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/segmentation","display_name":"Segmentation","score":0.8230166435241699},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7155276536941528},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6611486077308655},{"id":"https://openalex.org/keywords/lesion","display_name":"Lesion","score":0.5975370407104492},{"id":"https://openalex.org/keywords/cut","display_name":"Cut","score":0.5405413508415222},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5357031226158142},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5229552388191223},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4416045844554901},{"id":"https://openalex.org/keywords/region-growing","display_name":"Region growing","score":0.4280935525894165},{"id":"https://openalex.org/keywords/level-set","display_name":"Level set (data structures)","score":0.4259932339191437},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.3693477511405945},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.24176707863807678},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.09365931153297424}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8230166435241699},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7155276536941528},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6611486077308655},{"id":"https://openalex.org/C2781156865","wikidata":"https://www.wikidata.org/wiki/Q827023","display_name":"Lesion","level":2,"score":0.5975370407104492},{"id":"https://openalex.org/C5134670","wikidata":"https://www.wikidata.org/wiki/Q1626444","display_name":"Cut","level":4,"score":0.5405413508415222},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5357031226158142},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5229552388191223},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4416045844554901},{"id":"https://openalex.org/C206824153","wikidata":"https://www.wikidata.org/wiki/Q1169834","display_name":"Region growing","level":5,"score":0.4280935525894165},{"id":"https://openalex.org/C153008295","wikidata":"https://www.wikidata.org/wiki/Q6535093","display_name":"Level set (data structures)","level":2,"score":0.4259932339191437},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.3693477511405945},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.24176707863807678},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.09365931153297424}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008175","descriptor_name":"Lung Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D008175","descriptor_name":"Lung Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D008175","descriptor_name":"Lung Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D008175","descriptor_name":"Lung Neoplasms","qualifier_ui":"Q000473","qualifier_name":"pathology","is_major_topic":false},{"descriptor_ui":"D008175","descriptor_name":"Lung Neoplasms","qualifier_ui":"Q000473","qualifier_name":"pathology","is_major_topic":false},{"descriptor_ui":"D008175","descriptor_name":"Lung Neoplasms","qualifier_ui":"Q000473","qualifier_name":"pathology","is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/tmi.2015.2474119","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2015.2474119","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:26336121","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26336121","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":"IEEE transactions on medical imaging","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G1923445661","display_name":"\u9ad8\u9776\u5411PET/MRI\u53cc\u6a21\u6001\u5206\u5b50\u663e\u50cf\u63a2\u9488\u7684\u6784\u5efa\u53ca\u5176\u5728\u80ba\u764c\u65e9\u671f\u8bca\u65ad\u4e2d\u7684\u5e94\u7528\u7814\u7a76","funder_award_id":"81230030","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3779079207","display_name":null,"funder_award_id":"61302025","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3824205687","display_name":null,"funder_award_id":"61301002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4076610970","display_name":null,"funder_award_id":"81227901","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5137203102","display_name":"\u65e9\u671fCOPD\u5c0f\u8840\u7ba1\u548c\u5c0f\u6c14\u9053\u91cd\u5851\u6f14\u53d8\u89c4\u5f8b\u7684\u5b9a\u91cf\u5f71\u50cf\u5b66\u7814\u7a76","funder_award_id":"81370035","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7721118701","display_name":"\u57fa\u4e8e\u7ec4\u7ec7\u7279\u5f02\u6027\u7684\u5149\u5b66-\u6838\u7d20-CT\u591a\u6a21\u5f71\u50cf\u878d\u5408\u65b9\u6cd5\u4e0e\u6280\u672f","funder_award_id":"61231004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W49151124","https://openalex.org/W1637264906","https://openalex.org/W1977126844","https://openalex.org/W1986649315","https://openalex.org/W1988117153","https://openalex.org/W1992122542","https://openalex.org/W1994062553","https://openalex.org/W1995567168","https://openalex.org/W2016672701","https://openalex.org/W2025362214","https://openalex.org/W2027001755","https://openalex.org/W2035509863","https://openalex.org/W2037362135","https://openalex.org/W2045390724","https://openalex.org/W2046758959","https://openalex.org/W2051143518","https://openalex.org/W2068609255","https://openalex.org/W2072248589","https://openalex.org/W2078847121","https://openalex.org/W2083432437","https://openalex.org/W2103004421","https://openalex.org/W2108149355","https://openalex.org/W2109878240","https://openalex.org/W2110723426","https://openalex.org/W2113282793","https://openalex.org/W2131733682","https://openalex.org/W2132014319","https://openalex.org/W2132116135","https://openalex.org/W2134108967","https://openalex.org/W2137118100","https://openalex.org/W2137798983","https://openalex.org/W2140775860","https://openalex.org/W2146018860","https://openalex.org/W2149373586","https://openalex.org/W2149799076","https://openalex.org/W2153482625","https://openalex.org/W2157469204","https://openalex.org/W2161690989","https://openalex.org/W2161817637","https://openalex.org/W2166962164","https://openalex.org/W2321772193","https://openalex.org/W2324043694","https://openalex.org/W2534144589","https://openalex.org/W3148900723"],"related_works":["https://openalex.org/W1978085585","https://openalex.org/W2394279717","https://openalex.org/W2364730859","https://openalex.org/W2373659438","https://openalex.org/W3144569342","https://openalex.org/W2386644571","https://openalex.org/W2368273968","https://openalex.org/W2551987074","https://openalex.org/W4281943322","https://openalex.org/W2088651901"],"abstract_inverted_index":{"The":[0,82,152],"accurate":[1,192],"segmentation":[2,39,59,110,114,159,170,195],"of":[3,47,158],"lung":[4,14,48,193],"lesions":[5],"from":[6],"computed":[7],"tomography":[8],"(CT)":[9],"scans":[10],"is":[11,29],"important":[12],"for":[13,22,94,167],"cancer":[15],"research":[16],"and":[17,25,38,77,107,131,146,191],"can":[18,99,187],"offer":[19],"valuable":[20],"information":[21],"clinical":[23,133],"diagnosis":[24],"treatment.":[26],"However,":[27],"it":[28,98],"challenging":[30],"to":[31,44],"achieve":[32,188],"a":[33,53,63,101,108,122,155],"fully":[34],"automatic":[35,58,68],"lesion":[36,75,80,95,103,169,194],"detection":[37,104],"with":[40,62,112,141],"acceptable":[41],"accuracy":[42,111,160],"due":[43],"the":[45,78,126,163,184],"heterogeneity":[46],"lesions.":[49],"Here,":[50],"we":[51,181],"propose":[52],"novel":[54,185],"toboggan":[55],"based":[56],"growing":[57],"approach":[60,84],"(TBGA)":[61],"three-step":[64],"framework,":[65],"which":[66,118],"are":[67],"initial":[69],"seed":[70],"point":[71],"selection,":[72],"multi-constraints":[73],"3D":[74],"extraction":[76],"final":[79],"refinement.":[81],"new":[83,177],"does":[85],"not":[86],"require":[87],"any":[88],"human":[89],"interaction":[90],"or":[91],"training":[92],"dataset":[93,128,134],"detection,":[96],"yet":[97],"provide":[100],"high":[102],"sensitivity":[105],"(96.35%)":[106],"comparable":[109],"manual":[113],"(P":[115],">":[116],"0.05),":[117],"was":[119,171],"proved":[120],"by":[121],"series":[123],"assessments":[124],"using":[125,175],"LIDC-IDRI":[127],"(850":[129],"lesions)":[130],"in-house":[132],"(121":[135],"lesions).":[136],"We":[137],"also":[138],"compared":[139],"TBGA":[140,186],"commonly":[142],"used":[143],"level":[144],"set":[145],"skeleton":[147],"graph":[148],"cut":[149],"methods,":[150],"respectively.":[151],"results":[153],"indicated":[154],"significant":[156],"improvement":[157],".":[161],"Furthermore,":[162],"average":[164],"time":[165],"consumption":[166],"one":[168],"under":[172],"8":[173],"s":[174],"our":[176],"method.":[178],"In":[179],"conclusion,":[180],"believe":[182],"that":[183],"robust,":[189],"efficient":[190],"in":[196],"CT":[197],"images":[198],"automatically.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":8}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}