{"id":"https://openalex.org/W3159538208","doi":"https://doi.org/10.1109/access.2021.3074713","title":"Fully Automatic Model Based on SE-ResNet for Bone Age Assessment","display_name":"Fully Automatic Model Based on SE-ResNet for Bone Age Assessment","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3159538208","doi":"https://doi.org/10.1109/access.2021.3074713","mag":"3159538208"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3074713","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3074713","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09410217.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09410217.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110369704","display_name":"Jin He","orcid":"https://orcid.org/0000-0002-4142-2045"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]},{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin He","raw_affiliation_strings":["Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing, China","School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4142-2045","affiliations":[{"raw_affiliation_string":"Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing, China","institution_ids":["https://openalex.org/I4210139618"]},{"raw_affiliation_string":"School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100640399","display_name":"Dan Jiang","orcid":"https://orcid.org/0000-0001-6686-8054"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]},{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Jiang","raw_affiliation_strings":["Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing, China","School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6686-8054","affiliations":[{"raw_affiliation_string":"Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing, China","institution_ids":["https://openalex.org/I4210139618"]},{"raw_affiliation_string":"School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":41.8032,"has_fulltext":true,"cited_by_count":46,"citation_normalized_percentile":{"value":0.99797863,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"62460","last_page":"62466"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10992","display_name":"Forensic Anthropology and Bioarchaeology Studies","score":0.9965000152587891,"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":0.9965000152587891,"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":0.9919999837875366,"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":0.9909999966621399,"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/computer-science","display_name":"Computer science","score":0.7991150617599487},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6712801456451416},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6161462068557739},{"id":"https://openalex.org/keywords/lossless-compression","display_name":"Lossless compression","score":0.5330594778060913},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5275247693061829},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5137671232223511},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5055141448974609},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.4611726999282837},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.46116751432418823},{"id":"https://openalex.org/keywords/residual-neural-network","display_name":"Residual neural network","score":0.4600536525249481},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4376784563064575},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3881416320800781},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.3607527017593384},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.19643104076385498},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11794483661651611},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11548289656639099}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7991150617599487},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6712801456451416},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6161462068557739},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.5330594778060913},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5275247693061829},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5137671232223511},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5055141448974609},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.4611726999282837},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.46116751432418823},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.4600536525249481},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4376784563064575},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3881416320800781},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.3607527017593384},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.19643104076385498},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11794483661651611},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11548289656639099},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3074713","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3074713","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09410217.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a47fc33c1f7a48f3a4d06fe6f202215e","is_oa":true,"landing_page_url":"https://doaj.org/article/a47fc33c1f7a48f3a4d06fe6f202215e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 62460-62466 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3074713","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3074713","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09410217.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6078881638","display_name":null,"funder_award_id":"CX2019318","funder_id":"https://openalex.org/F4320321470","funder_display_name":"Beijing University of Posts and Telecommunications"}],"funders":[{"id":"https://openalex.org/F4320321470","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3159538208.pdf","grobid_xml":"https://content.openalex.org/works/W3159538208.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1521757480","https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1989831107","https://openalex.org/W2018148790","https://openalex.org/W2064365034","https://openalex.org/W2069821758","https://openalex.org/W2078561901","https://openalex.org/W2147310661","https://openalex.org/W2164243902","https://openalex.org/W2194775991","https://openalex.org/W2592765733","https://openalex.org/W2752782242","https://openalex.org/W2773607772","https://openalex.org/W2891282333","https://openalex.org/W2896437445","https://openalex.org/W2917452044","https://openalex.org/W2923494043","https://openalex.org/W2924654072","https://openalex.org/W2963420686","https://openalex.org/W2963466046","https://openalex.org/W2971291634","https://openalex.org/W2988013144","https://openalex.org/W3009813469","https://openalex.org/W3103400039","https://openalex.org/W3106450183","https://openalex.org/W3110487825","https://openalex.org/W3125372737","https://openalex.org/W4239814251","https://openalex.org/W6631190155","https://openalex.org/W6637373629"],"related_works":["https://openalex.org/W3196952692","https://openalex.org/W2984708981","https://openalex.org/W2948148442","https://openalex.org/W2461250372","https://openalex.org/W2394342941","https://openalex.org/W2169853506","https://openalex.org/W2547124190","https://openalex.org/W4300939921","https://openalex.org/W1558425494","https://openalex.org/W2350586049"],"abstract_inverted_index":{"Bone":[0],"age":[1],"assessment":[2],"(BAA)":[3],"based":[4,48,63],"on":[5,49,64,113],"hand":[6,139],"X-ray":[7,140],"imaging":[8],"is":[9,30,39,130],"a":[10,23,44,69,114,131],"common":[11],"clinical":[12],"practice":[13],"for":[14,43,142],"investigating":[15],"disorders":[16],"and":[17,33,55,68,134],"predicting":[18],"the":[19,26,78,83,91,97,101,122,127],"adult":[20],"height":[21],"of":[22,96],"child.":[24],"However,":[25],"traditional":[27],"manual":[28],"method":[29,120,129],"time":[31],"consuming":[32],"prone":[34],"to":[35,81,137],"obverse":[36],"variability.":[37],"There":[38],"an":[40,59],"urgent":[41],"need":[42],"fully":[45,132],"automatic":[46,133],"framework":[47],"deep":[50,71],"learning":[51],"with":[52,104],"high":[53],"performance":[54],"efficiency.":[56],"We":[57],"propose":[58],"end-to-end":[60],"BAA":[61],"model":[62,93,103],"lossless":[65],"image":[66,85],"compression":[67,79],"squeeze-and-excitation":[70],"residual":[72],"network":[73],"(SE-ResNet).":[74],"First,":[75],"we":[76],"apply":[77],"module":[80],"compress":[82],"raw":[84],"without":[86],"losing":[87],"important":[88],"features.":[89],"Second,":[90],"SE-ResNet-based":[92],"extracts":[94],"features":[95],"compressed":[98],"images.":[99],"Furthermore,":[100],"regression":[102],"improved":[105],"loss":[106],"function":[107],"predicts":[108],"bone":[109],"age.":[110],"The":[111],"experiments":[112],"public":[115],"dataset":[116],"reveal":[117],"that":[118],"our":[119],"outperforms":[121],"baseline":[123],"models.":[124],"In":[125],"conclusion,":[126],"presented":[128],"effective":[135],"solution":[136],"process":[138],"images":[141],"BAAs.":[143]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
