{"id":"https://openalex.org/W2070384695","doi":"https://doi.org/10.1117/12.2044297","title":"Multiple fuzzy object modeling improves sensitivity in automatic anatomy recognition","display_name":"Multiple fuzzy object modeling improves sensitivity in automatic anatomy recognition","publication_year":2014,"publication_date":"2014-03-21","ids":{"openalex":"https://openalex.org/W2070384695","doi":"https://doi.org/10.1117/12.2044297","mag":"2070384695"},"language":"en","primary_location":{"id":"doi:10.1117/12.2044297","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2044297","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/A5017698959","display_name":"Let\u00edcia Rittner","orcid":"https://orcid.org/0000-0001-8182-5554"},"institutions":[{"id":"https://openalex.org/I36788626","display_name":"California University of Pennsylvania","ror":"https://ror.org/01spssf70","country_code":"US","type":"education","lineage":["https://openalex.org/I36788626"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leticia Rittner","raw_affiliation_strings":["Univ. of Pennsylvania (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Pennsylvania (United States)","institution_ids":["https://openalex.org/I36788626"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065713856","display_name":"Jayaram K. Udupa","orcid":"https://orcid.org/0000-0002-7361-2927"},"institutions":[{"id":"https://openalex.org/I36788626","display_name":"California University of Pennsylvania","ror":"https://ror.org/01spssf70","country_code":"US","type":"education","lineage":["https://openalex.org/I36788626"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jayaram K. Udupa","raw_affiliation_strings":["Univ. of Pennsylvania (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Pennsylvania (United States)","institution_ids":["https://openalex.org/I36788626"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080030813","display_name":"Drew A. Torigian","orcid":"https://orcid.org/0000-0001-8999-9735"},"institutions":[{"id":"https://openalex.org/I36788626","display_name":"California University of Pennsylvania","ror":"https://ror.org/01spssf70","country_code":"US","type":"education","lineage":["https://openalex.org/I36788626"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Drew A. Torigian","raw_affiliation_strings":["Univ. of Pennsylvania (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Pennsylvania (United States)","institution_ids":["https://openalex.org/I36788626"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I36788626"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"9034","issue":null,"first_page":"90342U","last_page":"90342U"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9991999864578247,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7075797319412231},{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.5744549036026001},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5739668607711792},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5396208167076111},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4696570932865143},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.468448668718338},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4459567070007324},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.43337929248809814},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4118395149707794},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3875429630279541},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3574788272380829}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7075797319412231},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.5744549036026001},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5739668607711792},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5396208167076111},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4696570932865143},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.468448668718338},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4459567070007324},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.43337929248809814},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4118395149707794},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3875429630279541},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3574788272380829},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","level":1,"score":0.0},{"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:10.1117/12.2044297","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2044297","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":6,"referenced_works":["https://openalex.org/W1964162596","https://openalex.org/W2016381774","https://openalex.org/W2050255347","https://openalex.org/W2113017781","https://openalex.org/W6663103640","https://openalex.org/W6676786735"],"related_works":["https://openalex.org/W2365264209","https://openalex.org/W962203960","https://openalex.org/W2026999166","https://openalex.org/W2114275278","https://openalex.org/W1489511283","https://openalex.org/W2974914859","https://openalex.org/W2026565050","https://openalex.org/W2110244802","https://openalex.org/W2163728705","https://openalex.org/W949345935"],"abstract_inverted_index":{"Computerized":[0],"automatic":[1],"anatomy":[2],"recognition":[3,106],"(AAR)":[4],"is":[5,29,122,130],"an":[6,35],"essential":[7],"step":[8],"for":[9,73,83,118,133],"implementing":[10],"body-wide":[11],"quantitative":[12],"radiology":[13],"(QR).":[14],"Our":[15],"strategy":[16],"to":[17,66,124,138],"automatically":[18],"identify":[19],"and":[20,34,52,55],"delineate":[21],"various":[22],"organs":[23,142],"in":[24],"a":[25,77,89,115],"given":[26],"body":[27],"region":[28,98],"based":[30],"on":[31,88],"fuzzy":[32,70,80],"models":[33,81,112],"organ":[36,75],"hierarchy.":[37],"In":[38,60],"previous":[39],"years,":[40],"the":[41,61,68,84,96,128,146],"basic":[42],"algorithms":[43],"of":[44,79,92,95,99,114],"our":[45,102],"AAR":[46],"approach":[47,149],"-":[48,54],"model":[49,71,117,148],"building,":[50],"recognition,":[51],"delineation":[53],"their":[56],"evaluation":[57],"were":[58],"presented.":[59],"present":[62],"paper,":[63],"we":[64],"propose":[65],"replace":[67],"single":[69,116],"built":[72,82],"each":[74,119],"by":[76],"set":[78],"same":[85],"organ.":[86,120],"Based":[87],"dataset":[90],"composed":[91],"CT":[93],"images":[94],"Thorax":[97],"50":[100],"subjects,":[101],"experiments":[103],"indicate":[104],"that":[105,127,140],"performance":[107],"improves":[108],"when":[109],"using":[110],"multiple":[111,147],"instead":[113],"It":[121],"interesting":[123],"point":[125],"out":[126],"improvement":[129],"not":[131],"uniform":[132],"all":[134],"organs,":[135],"leading":[136],"us":[137],"conclude":[139],"some":[141],"will":[143],"benefit":[144],"from":[145],"more":[150],"than":[151],"others.":[152]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}