{"id":"https://openalex.org/W1982677792","doi":"https://doi.org/10.1117/12.2001531","title":"Customized hybrid level sets for automatic lung segmentation in chest x-ray images","display_name":"Customized hybrid level sets for automatic lung segmentation in chest x-ray images","publication_year":2013,"publication_date":"2013-03-13","ids":{"openalex":"https://openalex.org/W1982677792","doi":"https://doi.org/10.1117/12.2001531","mag":"1982677792"},"language":"en","primary_location":{"id":"doi:10.1117/12.2001531","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2001531","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":"conference-paper","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/A5059344826","display_name":"Sridharan Kamalakannan","orcid":"https://orcid.org/0000-0003-4106-9728"},"institutions":[{"id":"https://openalex.org/I2800548410","display_name":"United States National Library of Medicine","ror":"https://ror.org/0060t0j89","country_code":"US","type":"archive","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I2800548410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"S. Kamalakannan","raw_affiliation_strings":["National Library of Medicine (United States)","Texas Tech Univ. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Library of Medicine (United States)","institution_ids":["https://openalex.org/I2800548410"]},{"raw_affiliation_string":"Texas Tech Univ. (United States)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073995883","display_name":"Sameer Antani","orcid":"https://orcid.org/0000-0002-0040-1387"},"institutions":[{"id":"https://openalex.org/I2800548410","display_name":"United States National Library of Medicine","ror":"https://ror.org/0060t0j89","country_code":"US","type":"archive","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I2800548410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"S. Antani","raw_affiliation_strings":["National Library of Medicine (United States)","National Library of Medicine, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Library of Medicine (United States)","institution_ids":["https://openalex.org/I2800548410"]},{"raw_affiliation_string":"National Library of Medicine, United States","institution_ids":["https://openalex.org/I2800548410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073305817","display_name":"L. Rodney Long","orcid":"https://orcid.org/0000-0002-6218-7806"},"institutions":[{"id":"https://openalex.org/I2800548410","display_name":"United States National Library of Medicine","ror":"https://ror.org/0060t0j89","country_code":"US","type":"archive","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I2800548410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R. Long","raw_affiliation_strings":["National Library of Medicine (United States)","National Library of Medicine, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Library of Medicine (United States)","institution_ids":["https://openalex.org/I2800548410"]},{"raw_affiliation_string":"National Library of Medicine, United States","institution_ids":["https://openalex.org/I2800548410"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074891005","display_name":"Grid Thoma","orcid":"https://orcid.org/0000-0001-9836-2605"},"institutions":[{"id":"https://openalex.org/I2800548410","display_name":"United States National Library of Medicine","ror":"https://ror.org/0060t0j89","country_code":"US","type":"archive","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I2800548410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"G. Thoma","raw_affiliation_strings":["National Library of Medicine (United States)","National Library of Medicine, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Library of Medicine (United States)","institution_ids":["https://openalex.org/I2800548410"]},{"raw_affiliation_string":"National Library of Medicine, United States","institution_ids":["https://openalex.org/I2800548410"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2800548410"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08335657,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8669","issue":null,"first_page":"866939","last_page":"866939"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9975000023841858,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9975000023841858,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9908000230789185,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9789000153541565,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6608639359474182},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6371150016784668},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6229356527328491},{"id":"https://openalex.org/keywords/level-set","display_name":"Level set (data structures)","score":0.5898584723472595},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5206058025360107},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4994804859161377},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.495821088552475},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46757107973098755}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6608639359474182},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6371150016784668},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6229356527328491},{"id":"https://openalex.org/C153008295","wikidata":"https://www.wikidata.org/wiki/Q6535093","display_name":"Level set (data structures)","level":2,"score":0.5898584723472595},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5206058025360107},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4994804859161377},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.495821088552475},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46757107973098755},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2001531","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2001531","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1522196789","https://openalex.org/W2102683994","https://openalex.org/W2063813108","https://openalex.org/W2373659438","https://openalex.org/W2162755489","https://openalex.org/W2006136340","https://openalex.org/W1879755808","https://openalex.org/W70315200","https://openalex.org/W2926914344","https://openalex.org/W2164781768"],"abstract_inverted_index":{"A":[0],"chest":[1,57],"x-ray":[2,58],"screening":[3,39],"system":[4],"for":[5,106,140],"pulmonary":[6,86],"pathologies":[7],"such":[8,38],"as":[9],"tuberculosis":[10],"(TB)":[11],"is":[12,63,126,149,192],"of":[13,22,72,153,184,215,221,237],"paramount":[14],"importance":[15],"due":[16,65],"to":[17,66,109,120,165,179],"the":[18,52,73,89,122,141,146,169,185,202,211,233,238],"increasing":[19],"mortality":[20],"rate":[21],"patients":[23],"with":[24,85],"undiagnosed":[25],"TB,":[26],"especially":[27],"in":[28,134,177,205],"densely-populated":[29],"developing":[30,37],"countries.":[31],"As":[32],"a":[33,44,95,101,110,129,135,151,166,174,181,188,206],"first":[34,93],"step":[35,191],"toward":[36],"systems,":[40],"this":[41,115,225],"paper":[42],"presents":[43],"novel":[45],"computer":[46],"vision":[47],"module":[48],"that":[49,125],"automatically":[50],"segments":[51],"lungs":[53],"from":[54],"posteroanterior":[55],"digital":[56],"images.":[59],"The":[60,227],"segmentation":[61,183,190],"task":[62],"non-trivial,":[64],"poor":[67],"image":[68,157],"contrast":[69],"and":[70,80,159,200,235],"occlusion":[71],"lung":[74,96,118],"region":[75],"by":[76,81,99,194],"ribs,":[77],"clavicle,":[78],"heart,":[79],"non-TB":[82],"abnormalities":[83],"associated":[84],"diseases.":[87],"In":[88],"proposed":[90,239],"procedure,":[91],"we":[92,113],"compute":[94],"shape":[97,119,162,197],"model":[98],"employing":[100],"level":[102,123,147,156,161,170,203],"set":[103,124,148,171,204],"based":[104,127],"technique":[105],"registration":[107],"up":[108,164],"homography.":[111],"Next,":[112],"use":[114],"computed":[116],"mean":[117],"initialize":[121],"on":[128],"best":[130],"fit":[131],"measure":[132],"obtained":[133],"heuristically":[136],"estimated":[137],"search":[138],"space":[139],"projective":[142],"transform":[143],"parameters.":[144],"Once":[145],"initialized,":[150],"suite":[152],"customized":[154],"lower":[155,175],"features":[158,163],"higher":[160,207],"homography":[167],"evolve":[168],"function":[172],"at":[173],"resolution":[176],"order":[178],"achieve":[180],"coarse":[182],"lungs.":[186],"Finally,":[187],"fine":[189],"performed":[193],"adding":[195],"additional":[196],"variation":[198],"constraints":[199],"evolving":[201],"resolution.":[208],"We":[209],"processed":[210],"standard":[212],"Japanese":[213],"Society":[214],"Radiological":[216],"Technology":[217],"(JSRT)":[218],"dataset,":[219],"comprised":[220],"247":[222],"images,":[223],"using":[224],"scheme.":[226],"promising":[228],"results":[229],"(92%":[230],"accuracy)":[231],"demonstrate":[232],"viability":[234],"efficacy":[236],"approach.":[240]},"counts_by_year":[],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}
