{"id":"https://openalex.org/W3022033765","doi":"https://doi.org/10.1109/i2mtc43012.2020.9128460","title":"Bone age assessment based on phalanx radiograms","display_name":"Bone age assessment based on phalanx radiograms","publication_year":2020,"publication_date":"2020-05-01","ids":{"openalex":"https://openalex.org/W3022033765","doi":"https://doi.org/10.1109/i2mtc43012.2020.9128460","mag":"3022033765"},"language":"en","primary_location":{"id":"doi:10.1109/i2mtc43012.2020.9128460","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc43012.2020.9128460","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","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/A5024549249","display_name":"Chih\u2010Yen Chen","orcid":"https://orcid.org/0000-0001-6519-3614"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Chih-Yen Chen","raw_affiliation_strings":["School of Electronic Engineering and Computer Science, Queen Mary University of London, London, U.K"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering and Computer Science, Queen Mary University of London, London, U.K","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100678562","display_name":"Lijuan Wang","orcid":"https://orcid.org/0000-0001-6505-7612"},"institutions":[{"id":"https://openalex.org/I20581793","display_name":"University of Kent","ror":"https://ror.org/00xkeyj56","country_code":"GB","type":"education","lineage":["https://openalex.org/I20581793"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lijuan Wang","raw_affiliation_strings":["School of Engineering and Digital Arts, University of Kent, Canterbury, Kent, U.K"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Digital Arts, University of Kent, Canterbury, Kent, U.K","institution_ids":["https://openalex.org/I20581793"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062994447","display_name":"Chi\u2010Wen Hsieh","orcid":"https://orcid.org/0000-0002-7006-8794"},"institutions":[{"id":"https://openalex.org/I183570559","display_name":"National Chiayi University","ror":"https://ror.org/04gknbs13","country_code":"TW","type":"education","lineage":["https://openalex.org/I183570559"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chi-Wen Hsieh","raw_affiliation_strings":["Department of Electrical Engineering, National Chiayi University, Chiayi, Taiwan (R.O.C.)"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Chiayi University, Chiayi, Taiwan (R.O.C.)","institution_ids":["https://openalex.org/I183570559"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5024549249"],"corresponding_institution_ids":["https://openalex.org/I166337079"],"apc_list":null,"apc_paid":null,"fwci":1.5491,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.85705605,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"17","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10992","display_name":"Forensic Anthropology and Bioarchaeology Studies","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/1204","display_name":"Archeology"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10992","display_name":"Forensic Anthropology and Bioarchaeology Studies","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/1204","display_name":"Archeology"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11363","display_name":"Dental Radiography and Imaging","score":0.9721999764442444,"subfield":{"id":"https://openalex.org/subfields/3504","display_name":"Oral Surgery"},"field":{"id":"https://openalex.org/fields/35","display_name":"Dentistry"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9710000157356262,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bone-age","display_name":"Bone age","score":0.8046244382858276},{"id":"https://openalex.org/keywords/phalanx","display_name":"Phalanx","score":0.7204402685165405},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.612896740436554},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5189799666404724},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4655248820781708},{"id":"https://openalex.org/keywords/age-groups","display_name":"Age groups","score":0.4255889058113098},{"id":"https://openalex.org/keywords/orthodontics","display_name":"Orthodontics","score":0.4055296778678894},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3752634525299072},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35197770595550537},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3396400213241577},{"id":"https://openalex.org/keywords/anatomy","display_name":"Anatomy","score":0.3035069704055786}],"concepts":[{"id":"https://openalex.org/C89551170","wikidata":"https://www.wikidata.org/wiki/Q1777274","display_name":"Bone age","level":2,"score":0.8046244382858276},{"id":"https://openalex.org/C139542699","wikidata":"https://www.wikidata.org/wiki/Q180335","display_name":"Phalanx","level":2,"score":0.7204402685165405},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.612896740436554},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5189799666404724},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4655248820781708},{"id":"https://openalex.org/C2986834420","wikidata":"https://www.wikidata.org/wiki/Q5932254","display_name":"Age groups","level":2,"score":0.4255889058113098},{"id":"https://openalex.org/C29694066","wikidata":"https://www.wikidata.org/wiki/Q118301","display_name":"Orthodontics","level":1,"score":0.4055296778678894},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3752634525299072},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35197770595550537},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3396400213241577},{"id":"https://openalex.org/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","level":1,"score":0.3035069704055786},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/i2mtc43012.2020.9128460","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc43012.2020.9128460","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","raw_type":"proceedings-article"},{"id":"pmh:oai:kar.kent.ac.uk:80848","is_oa":false,"landing_page_url":"https://kar.kent.ac.uk/80848/","pdf_url":null,"source":{"id":"https://openalex.org/S4377196264","display_name":"Kent Academic Repository (University of Kent)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I20581793","host_organization_name":"University of Kent","host_organization_lineage":["https://openalex.org/I20581793"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference or workshop item"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1963985519","https://openalex.org/W1980616111","https://openalex.org/W1988445395","https://openalex.org/W1989831107","https://openalex.org/W1996103192","https://openalex.org/W2015034007","https://openalex.org/W2018148790","https://openalex.org/W2110373411","https://openalex.org/W2130164355","https://openalex.org/W2146904198","https://openalex.org/W2147310661","https://openalex.org/W2171827933","https://openalex.org/W2208488269","https://openalex.org/W2267766002","https://openalex.org/W2566111358","https://openalex.org/W2766766852","https://openalex.org/W2891282333","https://openalex.org/W2896437445","https://openalex.org/W6654957525","https://openalex.org/W6755241488"],"related_works":["https://openalex.org/W2293067732","https://openalex.org/W2010354477","https://openalex.org/W2081843513","https://openalex.org/W2321585096","https://openalex.org/W3028886747","https://openalex.org/W2199146992","https://openalex.org/W1989792824","https://openalex.org/W2734830518","https://openalex.org/W2384863224","https://openalex.org/W2094766543"],"abstract_inverted_index":{"To":[0],"identify":[1],"the":[2,32,47,53,69,85,105,108,145,150,158],"growth":[3],"status":[4],"of":[5,28,34,57,63,87,107,156,161],"children,":[6],"more":[7,9],"and":[8,60,76,167],"bone":[10,55],"age":[11],"assessment":[12],"(BAA)":[13],"systems":[14],"based":[15],"on":[16,144],"Tanner\u2013":[17],"Whitehouse":[18],"(TW)":[19],"method":[20],"have":[21],"been":[22],"developed":[23],"to":[24,40,103,125,135],"estimate":[25],"skeletal":[26,88],"maturity":[27],"children.":[29],"Therefore,":[30],"with":[31,96,163,169],"concept":[33],"TW":[35],"method,":[36],"our":[37],"aim":[38],"is":[39,101,154],"develop":[41],"a":[42],"useful":[43],"BAA":[44,152],"system":[45,153],"for":[46,84],"phalanx":[48],"radiograms.":[49,72],"In":[50],"this":[51],"study,":[52],"phalangeal":[54],"regions":[56,62],"interest":[58,64],"(PROIs)":[59],"epiphyseal/metaphyseal":[61],"(EMROIs)":[65],"are":[66,80],"segmented":[67],"from":[68,82,118,123],"two":[70],"left-hand":[71,114],"The":[73,90,110,139],"textural,":[74],"morphological":[75],"shape":[77],"descriptor":[78],"features":[79],"extracted":[81],"EMROIs":[83],"quantization":[86],"maturity.":[89],"fuzzy":[91],"logic":[92],"rule":[93],"in":[94],"conjunction":[95],"principal":[97],"component":[98],"analysis":[99],"(PCA)":[100],"applied":[102],"construct":[104],"model":[106],"classification.":[109],"database":[111],"comprising":[112],"1550":[113],"radiograms":[115],"were":[116,133],"collected":[117],"normal":[119],"female":[120],"children":[121],"aging":[122],"2":[124],"16":[126],"years.":[127],"For":[128],"each":[129],"age,":[130],"15":[131],"images":[132],"used":[134],"constitute":[136],"training":[137],"data.":[138],"classification":[140],"results":[141],"by":[142],"testing":[143],"rest":[146],"data":[147],"demonstrate":[148],"that":[149],"proposed":[151],"capable":[155],"providing":[157],"correct":[159],"rate":[160],"71.17%":[162],"1":[164],"year":[165,171],"tolerance":[166],"89.74%":[168],"1.5":[170],"tolerance.":[172]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}