{"id":"https://openalex.org/W2045485466","doi":"https://doi.org/10.1117/12.2082410","title":"Segmentation of the whole breast from low-dose chest CT images","display_name":"Segmentation of the whole breast from low-dose chest CT images","publication_year":2015,"publication_date":"2015-03-20","ids":{"openalex":"https://openalex.org/W2045485466","doi":"https://doi.org/10.1117/12.2082410","mag":"2045485466"},"language":"en","primary_location":{"id":"doi:10.1117/12.2082410","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2082410","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","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/A5100319073","display_name":"Shuang Liu","orcid":"https://orcid.org/0000-0001-8766-7235"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shuang Liu","raw_affiliation_strings":["Cornell Univ. (United States)","Cornell Univ. United States"],"affiliations":[{"raw_affiliation_string":"Cornell Univ. (United States)","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"Cornell Univ. United States","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004022151","display_name":"Mary Salvatore","orcid":"https://orcid.org/0000-0002-1429-5749"},"institutions":[{"id":"https://openalex.org/I98704320","display_name":"Icahn School of Medicine at Mount Sinai","ror":"https://ror.org/04a9tmd77","country_code":"US","type":"education","lineage":["https://openalex.org/I1320796813","https://openalex.org/I98704320"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mary Salvatore","raw_affiliation_strings":["Icahn School of Medicine at Mount Sinai (United States)"],"affiliations":[{"raw_affiliation_string":"Icahn School of Medicine at Mount Sinai (United States)","institution_ids":["https://openalex.org/I98704320"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036008725","display_name":"David F. Yankelevitz","orcid":"https://orcid.org/0000-0001-7364-4294"},"institutions":[{"id":"https://openalex.org/I98704320","display_name":"Icahn School of Medicine at Mount Sinai","ror":"https://ror.org/04a9tmd77","country_code":"US","type":"education","lineage":["https://openalex.org/I1320796813","https://openalex.org/I98704320"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David F. Yankelevitz","raw_affiliation_strings":["Icahn School of Medicine at Mount Sinai (United States)"],"affiliations":[{"raw_affiliation_string":"Icahn School of Medicine at Mount Sinai (United States)","institution_ids":["https://openalex.org/I98704320"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008905381","display_name":"Claudia I. Henschke","orcid":"https://orcid.org/0000-0002-6085-5305"},"institutions":[{"id":"https://openalex.org/I98704320","display_name":"Icahn School of Medicine at Mount Sinai","ror":"https://ror.org/04a9tmd77","country_code":"US","type":"education","lineage":["https://openalex.org/I1320796813","https://openalex.org/I98704320"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Claudia I. Henschke","raw_affiliation_strings":["Icahn School of Medicine at Mount Sinai (United States)"],"affiliations":[{"raw_affiliation_string":"Icahn School of Medicine at Mount Sinai (United States)","institution_ids":["https://openalex.org/I98704320"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060527966","display_name":"Anthony P. Reeves","orcid":"https://orcid.org/0000-0002-1451-3080"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anthony P. Reeves","raw_affiliation_strings":["Cornell Univ. (United States)","Cornell Univ. United States"],"affiliations":[{"raw_affiliation_string":"Cornell Univ. (United States)","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"Cornell Univ. United States","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100319073"],"corresponding_institution_ids":["https://openalex.org/I205783295"],"apc_list":null,"apc_paid":null,"fwci":3.1244,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.92765727,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"9414","issue":null,"first_page":"94140I","last_page":"94140I"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11361","display_name":"Digital Radiography and Breast Imaging","score":0.9994000196456909,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9973000288009644,"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":0.7768176198005676},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.722661018371582},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.677049994468689},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5689940452575684},{"id":"https://openalex.org/keywords/sagittal-plane","display_name":"Sagittal plane","score":0.552821934223175},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.5449799299240112},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.528947114944458},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45920875668525696},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.45638492703437805},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.439919114112854},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.39169949293136597},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3460838198661804},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.25227051973342896}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7768176198005676},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.722661018371582},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.677049994468689},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5689940452575684},{"id":"https://openalex.org/C178910020","wikidata":"https://www.wikidata.org/wiki/Q2211994","display_name":"Sagittal plane","level":2,"score":0.552821934223175},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.5449799299240112},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.528947114944458},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45920875668525696},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.45638492703437805},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.439919114112854},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.39169949293136597},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3460838198661804},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.25227051973342896},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2082410","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2082410","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W96995336","https://openalex.org/W2002798983","https://openalex.org/W2013733315","https://openalex.org/W2022611268","https://openalex.org/W2026242200","https://openalex.org/W2118867739","https://openalex.org/W2124391915","https://openalex.org/W2170776495","https://openalex.org/W6650981094"],"related_works":["https://openalex.org/W2053950117","https://openalex.org/W4295532600","https://openalex.org/W2063823869","https://openalex.org/W2047973478","https://openalex.org/W4391250048","https://openalex.org/W4313044406","https://openalex.org/W3201505834","https://openalex.org/W4206010360","https://openalex.org/W3110400269","https://openalex.org/W2157102420"],"abstract_inverted_index":{"The":[0,68,119,153,167,198],"segmentation":[1,72,160,178,215],"of":[2,129,133,138,146,209,223],"whole":[3,49,70,158],"breast":[4,12,23,35,50,71,75,112,140,159],"serves":[5],"as":[6,61,78,80],"the":[7,22,48,97,134,139,144,150,177,213],"first":[8],"step":[9],"towards":[10],"automated":[11,44,69,214],"lesion":[13,81],"detection.":[14],"It":[15],"is":[16,26,169,203],"also":[17],"necessary":[18],"for":[19,34,89,111,195],"automatically":[20],"assessing":[21],"density,":[24],"which":[25,57],"considered":[27],"to":[28,46,123],"be":[29,124],"an":[30,62,162],"important":[31],"risk":[32,109],"factor":[33],"cancer.":[36],"In":[37],"this":[38],"paper":[39],"we":[40],"present":[41],"a":[42,185,206,224],"fully":[43],"algorithm":[45,155,216],"segment":[47],"in":[51,83,131,141],"low-dose":[52],"chest":[53],"CT":[54],"images":[55],"(LDCT),":[56],"has":[58],"been":[59],"recommended":[60],"annual":[63],"lung":[64],"cancer":[65,113],"screening":[66],"test.":[67],"and":[73,136,143,191],"potential":[74],"density":[76],"readings":[77],"well":[79],"detection":[82],"LDCT":[84,94,142,173],"will":[85],"provide":[86],"useful":[87],"information":[88],"women":[90],"who":[91,99],"have":[92,100],"received":[93],"screening,":[95,104],"especially":[96],"ones":[98],"not":[101],"undergone":[102],"mammographic":[103],"by":[105,175,184],"providing":[106],"them":[107],"additional":[108,116],"indicators":[110],"with":[114,179,205,220],"no":[115],"radiation":[117],"exposure.":[118],"two":[120,192],"main":[121],"challenges":[122],"addressed":[125],"are":[126],"significant":[127],"range":[128],"variations":[130],"terms":[132],"shape":[135],"location":[137],"separation":[145],"pectoral":[147],"muscles":[148],"from":[149],"glandular":[151],"tissues.":[152],"presented":[154],"achieves":[156,217],"robust":[157],"using":[161],"anatomy":[163],"directed":[164],"rule-based":[165],"method.":[166],"evaluation":[168],"performed":[170],"on":[171,187],"20":[172],"scans":[174],"comparing":[176],"ground":[180],"truth":[181],"manually":[182],"annotated":[183],"radiologist":[186],"one":[188],"axial":[189],"slice":[190],"sagittal":[193],"slices":[194],"each":[196],"scan.":[197],"resulting":[199],"average":[200],"Dice":[201],"coefficient":[202],"0.880":[204],"standard":[207],"deviation":[208],"0.058,":[210],"demonstrating":[211],"that":[212],"results":[218],"consistent":[219],"manual":[221],"annotations":[222],"radiologist.":[225]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2}],"updated_date":"2026-03-13T14:20:09.374765","created_date":"2025-10-10T00:00:00"}