{"id":"https://openalex.org/W2047683926","doi":"https://doi.org/10.1109/dicta.2013.6691494","title":"Context Curves for Classification of Lung Nodule Images","display_name":"Context Curves for Classification of Lung Nodule Images","publication_year":2013,"publication_date":"2013-11-01","ids":{"openalex":"https://openalex.org/W2047683926","doi":"https://doi.org/10.1109/dicta.2013.6691494","mag":"2047683926"},"language":"en","primary_location":{"id":"doi:10.1109/dicta.2013.6691494","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2013.6691494","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","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/A5100403473","display_name":"Fan Zhang","orcid":"https://orcid.org/0000-0002-5032-6039"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Fan Zhang","raw_affiliation_strings":["BMIT Research Group, University of Sydney, Australia","BMIT Res. group, Univ. of Sydney, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"BMIT Research Group, University of Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]},{"raw_affiliation_string":"BMIT Res. group, Univ. of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041567418","display_name":"Yang Song","orcid":"https://orcid.org/0000-0003-1283-1672"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yang Song","raw_affiliation_strings":["BMIT Research Group, University of Sydney, Australia","BMIT Res. group, Univ. of Sydney, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"BMIT Research Group, University of Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]},{"raw_affiliation_string":"BMIT Res. group, Univ. of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076697411","display_name":"Weidong Cai","orcid":"https://orcid.org/0000-0003-3706-8896"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Weidong Cai","raw_affiliation_strings":["BMIT Research Group, University of Sydney, Australia","BMIT Res. group, Univ. of Sydney, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"BMIT Research Group, University of Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]},{"raw_affiliation_string":"BMIT Res. group, Univ. of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103063753","display_name":"Yun Zhou","orcid":"https://orcid.org/0000-0001-8635-4675"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yun Zhou","raw_affiliation_strings":["The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, USA","Sch. of Med., Russell H. Morgan Dept. of Radiol. & Radiol. Sci., Johns Hopkins Univ., Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, USA","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"Sch. of Med., Russell H. Morgan Dept. of Radiol. & Radiol. Sci., Johns Hopkins Univ., Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102864042","display_name":"Shimin Shan","orcid":"https://orcid.org/0000-0003-0864-7258"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shimin Shan","raw_affiliation_strings":["School of Software, Dalian University of Technolog, China","School of Software, Dalian University of Technology,DaLian,China"],"affiliations":[{"raw_affiliation_string":"School of Software, Dalian University of Technolog, China","institution_ids":["https://openalex.org/I27357992"]},{"raw_affiliation_string":"School of Software, Dalian University of Technology,DaLian,China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068891693","display_name":"Dagan Feng","orcid":"https://orcid.org/0000-0002-3381-214X"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Dagan Feng","raw_affiliation_strings":["BMIT Research Group, University of Sydney, Australia","BMIT Res. group, Univ. of Sydney, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"BMIT Research Group, University of Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]},{"raw_affiliation_string":"BMIT Res. group, Univ. of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100403473"],"corresponding_institution_ids":["https://openalex.org/I129604602"],"apc_list":null,"apc_paid":null,"fwci":2.64014347,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.8879597,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"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":0.9966999888420105,"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":0.9966999888420105,"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":0.9944999814033508,"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":0.989799976348877,"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/discriminative-model","display_name":"Discriminative model","score":0.8060370683670044},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.7553648352622986},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7186647653579712},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6807559132575989},{"id":"https://openalex.org/keywords/nodule","display_name":"Nodule (geology)","score":0.6807100772857666},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6746498346328735},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6521085500717163},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5332346558570862},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5259347558021545},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.42082852125167847},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41830840706825256},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.40108516812324524},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.05551430583000183}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8060370683670044},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.7553648352622986},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7186647653579712},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6807559132575989},{"id":"https://openalex.org/C2776731575","wikidata":"https://www.wikidata.org/wiki/Q2916245","display_name":"Nodule (geology)","level":2,"score":0.6807100772857666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6746498346328735},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6521085500717163},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5332346558570862},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5259347558021545},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.42082852125167847},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41830840706825256},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.40108516812324524},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.05551430583000183},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dicta.2013.6691494","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2013.6691494","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W9958333","https://openalex.org/W118842915","https://openalex.org/W146996797","https://openalex.org/W1508404128","https://openalex.org/W1695355397","https://openalex.org/W1787683252","https://openalex.org/W1872131228","https://openalex.org/W1930352176","https://openalex.org/W1975020933","https://openalex.org/W1982601680","https://openalex.org/W1985289613","https://openalex.org/W1989337749","https://openalex.org/W1997058394","https://openalex.org/W2013290608","https://openalex.org/W2040245343","https://openalex.org/W2101610532","https://openalex.org/W2110261828","https://openalex.org/W2117172213","https://openalex.org/W2117905323","https://openalex.org/W2122692815","https://openalex.org/W2133145320","https://openalex.org/W2134108967","https://openalex.org/W2137798983","https://openalex.org/W2148704119","https://openalex.org/W2153635508","https://openalex.org/W2155662634","https://openalex.org/W2160764363","https://openalex.org/W2168356304","https://openalex.org/W2395422030","https://openalex.org/W4256741478","https://openalex.org/W4285719527","https://openalex.org/W6600389112","https://openalex.org/W6630399218","https://openalex.org/W6637467091","https://openalex.org/W6679859549","https://openalex.org/W6712359574"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W156213964","https://openalex.org/W2761785940","https://openalex.org/W2050960118","https://openalex.org/W2129933262","https://openalex.org/W2565656575","https://openalex.org/W4390143830"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,105,118],"feature-based":[4],"imaging":[5],"classification":[6],"method":[7,32,132],"is":[8,115],"presented":[9],"to":[10],"classify":[11],"the":[12,35,57,76,84,88,91,101,123,126,130],"lung":[13,41,134],"nodules":[14],"in":[15],"low":[16],"dose":[17],"computed":[18],"tomography":[19],"(LDCT)":[20],"slides":[21],"into":[22,59,80],"four":[23],"categories:":[24],"well-circumscribed,":[25],"vascularized,":[26],"juxta-pleural":[27],"and":[28,43,47,61,110,122],"pleural-tail.":[29],"The":[30,113],"proposed":[31,131],"focuses":[33],"on":[34,64,117,133],"feature":[36,81],"design,":[37],"which":[38,55,74],"describes":[39],"both":[40],"nodule":[42,135],"surrounding":[44],"context":[45,71,93,102],"information,":[46],"contains":[48],"two":[49],"main":[50],"stages:":[51],"(1)":[52],"superpixel":[53,77],"labeling,":[54],"labels":[56],"pixels":[58],"foreground":[60],"background":[62],"based":[63],"an":[65],"image":[66],"patch":[67],"division":[68],"approach,":[69],"(2)":[70],"curve":[72,103],"calculation,":[73],"transfers":[75],"labeling":[78],"result":[79],"vector.":[82],"While":[83],"first":[85],"stage":[86],"preprocesses":[87],"image,":[89],"extracting":[90],"major":[92],"anatomical":[94],"structures":[95],"for":[96,108],"each":[97],"type":[98],"of":[99,129],"nodules,":[100],"provides":[104],"discriminative":[106],"description":[107],"intra-":[109],"inter-type":[111],"nodules.":[112],"evaluation":[114],"conducted":[116],"publicly":[119],"available":[120],"dataset":[121],"results":[124],"indicate":[125],"promising":[127],"performance":[128],"classification.":[136]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}