{"id":"https://openalex.org/W3011092637","doi":"https://doi.org/10.1117/12.2550010","title":"Multi-atlas-based tissue identification in the lower leg using pQCT","display_name":"Multi-atlas-based tissue identification in the lower leg using pQCT","publication_year":2020,"publication_date":"2020-03-10","ids":{"openalex":"https://openalex.org/W3011092637","doi":"https://doi.org/10.1117/12.2550010","mag":"3011092637"},"language":"en","primary_location":{"id":"doi:10.1117/12.2550010","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2550010","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Image Processing","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/A5074243216","display_name":"Sokratis Makrogiannis","orcid":"https://orcid.org/0000-0003-0316-3529"},"institutions":[{"id":"https://openalex.org/I126548940","display_name":"Delaware State University","ror":"https://ror.org/03g35dg18","country_code":"US","type":"education","lineage":["https://openalex.org/I126548940"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sokratis Makrogiannis","raw_affiliation_strings":["Delaware State Univ. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Delaware State Univ. (United States)","institution_ids":["https://openalex.org/I126548940"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065761265","display_name":"Azubuike Okorie","orcid":"https://orcid.org/0000-0002-1348-3166"},"institutions":[{"id":"https://openalex.org/I126548940","display_name":"Delaware State University","ror":"https://ror.org/03g35dg18","country_code":"US","type":"education","lineage":["https://openalex.org/I126548940"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Azubuike Okorie","raw_affiliation_strings":["Delaware State Univ. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Delaware State Univ. (United States)","institution_ids":["https://openalex.org/I126548940"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113959497","display_name":"Taposh Biswas","orcid":null},"institutions":[{"id":"https://openalex.org/I126548940","display_name":"Delaware State University","ror":"https://ror.org/03g35dg18","country_code":"US","type":"education","lineage":["https://openalex.org/I126548940"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Taposh Biswas","raw_affiliation_strings":["Delaware State Univ. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Delaware State Univ. (United States)","institution_ids":["https://openalex.org/I126548940"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048196698","display_name":"Luigi Ferrucci","orcid":"https://orcid.org/0000-0002-6273-1613"},"institutions":[{"id":"https://openalex.org/I1299303238","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Luigi Ferrucci","raw_affiliation_strings":["National Institutes of Health (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institutes of Health (United States)","institution_ids":["https://openalex.org/I1299303238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.02283758,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"120","last_page":"120"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9988999962806702,"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"}},"topics":[{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9988999962806702,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9986000061035156,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9984999895095825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6894783973693848},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6120023727416992},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5850062370300293},{"id":"https://openalex.org/keywords/quantitative-computed-tomography","display_name":"Quantitative computed tomography","score":0.5220601558685303},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.48033085465431213},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.478437215089798},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4424033463001251},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43480557203292847},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.420177161693573},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.41247493028640747},{"id":"https://openalex.org/keywords/biomedical-engineering","display_name":"Biomedical engineering","score":0.34724265336990356},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2007777988910675},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15472376346588135}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6894783973693848},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6120023727416992},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5850062370300293},{"id":"https://openalex.org/C2777425516","wikidata":"https://www.wikidata.org/wiki/Q17083560","display_name":"Quantitative computed tomography","level":4,"score":0.5220601558685303},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.48033085465431213},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.478437215089798},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4424033463001251},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43480557203292847},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.420177161693573},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.41247493028640747},{"id":"https://openalex.org/C136229726","wikidata":"https://www.wikidata.org/wiki/Q327092","display_name":"Biomedical engineering","level":1,"score":0.34724265336990356},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2007777988910675},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15472376346588135},{"id":"https://openalex.org/C2776541429","wikidata":"https://www.wikidata.org/wiki/Q165328","display_name":"Osteoporosis","level":2,"score":0.0},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0},{"id":"https://openalex.org/C2779329777","wikidata":"https://www.wikidata.org/wiki/Q2304401","display_name":"Bone density","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2550010","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2550010","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"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":0,"referenced_works":[],"related_works":["https://openalex.org/W2007297965","https://openalex.org/W2395988836","https://openalex.org/W2773392641","https://openalex.org/W4238127743","https://openalex.org/W2080535989","https://openalex.org/W2734585990","https://openalex.org/W2192435767","https://openalex.org/W2153667234","https://openalex.org/W2157102420","https://openalex.org/W2789768443"],"abstract_inverted_index":{"Accurate":[0],"and":[1,11,49,58,74,83,95,111,129,144,168,183,207],"reproducible":[2],"tissue":[3,72],"identification":[4,73],"techniques":[5,34,125],"are":[6,35,80],"essential":[7],"for":[8,38,50,71,103,191,202,240],"understanding":[9],"structural":[10],"functional":[12],"changes":[13,41],"that":[14,106,150,221],"either":[15],"occur":[16],"naturally":[17],"with":[18,166,226,242],"aging,":[19],"or":[20,25],"because":[21],"of":[22,40,53,55,77,135,141,172,198,234],"chronic":[23],"disease,":[24],"in":[26,42,92,132],"response":[27],"to":[28,45,126,145],"intervention":[29],"therapies.":[30],"These":[31],"image":[32,108],"analysis":[33],"frequently":[36],"utilized":[37],"characterization":[39],"bone":[43],"architecture":[44],"assess":[46],"fracture":[47],"risk,":[48],"the":[51,136,147,156,173,196],"assessment":[52],"loss":[54],"muscle":[56],"mass":[57],"strength":[59],"defined":[60],"as":[61,114],"sarcopenia.":[62],"Peripheral":[63],"quantitative":[64],"computed":[65],"tomography":[66],"(pQCT)":[67],"is":[68,99],"widely":[69],"employed":[70,160],"analysis.":[75],"Advantages":[76],"pQCT":[78,133],"scanners":[79],"compactness,":[81],"portability,":[82],"low":[84],"radiation":[85],"dose.":[86],"However,":[87],"these":[88],"characteristics":[89],"imply":[90],"limitations":[91,110],"spatial":[93],"resolution":[94],"SNR.":[96],"Therefore,":[97],"there":[98],"still":[100],"a":[101,169],"need":[102],"segmentation":[104,123],"methods":[105],"address":[107,146],"quality":[109,244],"artifacts":[112],"such":[113],"patient":[115],"motion.":[116],"In":[117],"this":[118],"paper,":[119],"we":[120,159],"introduce":[121],"multi-atlas":[122],"(MAS)":[124],"identify":[127],"soft":[128],"hard":[130],"tissues":[131],"scans":[134,241],"proximal":[137],"tibia":[138],"(~":[139],"66%":[140],"tibial":[142],"length)":[143],"above":[148],"factors":[149],"limit":[151],"delineation":[152],"accuracy.":[153],"To":[154],"calculate":[155],"deformation":[157,163],"fields,":[158],"multi-grid":[161],"free-form":[162],"(FFD)":[164],"models":[165],"B-splines":[167],"symmetric":[170],"extension":[171],"log-domain":[174],"diffeomorphic":[175],"demons":[176],"(SDD).":[177],"We":[178,194],"then":[179],"applied":[180],"majority":[181],"voting":[182],"Simultaneous":[184],"Truth":[185],"And":[186],"Performance":[187],"Level":[188],"Estimation":[189],"(STAPLE)":[190],"label":[192,209],"fusion.":[193],"compared":[195],"results":[197,219],"our":[199,222],"MAS":[200],"methodology":[201],"each":[203,208],"deformable":[204],"registration":[205],"model":[206],"fusion":[210],"method,":[211],"using":[212],"Dice":[213],"similarity":[214],"coefficient":[215],"scores":[216],"(DSC).":[217],"The":[218],"show":[220],"technique":[223],"utilizing":[224],"SDD":[225],"STAPLE":[227],"produces":[228],"very":[229],"good":[230],"accuracy":[231],"(DSC":[232],"mean":[233],"0.868)":[235],"over":[236],"all":[237],"tissues,":[238],"even":[239],"considerable":[243],"degradations":[245],"caused":[246],"by":[247],"motion":[248],"artifacts.":[249]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
