{"id":"https://openalex.org/W4287890640","doi":"https://doi.org/10.1109/tim.2022.3193711","title":"CFJLNet: Coarse and Fine Feature Joint Learning Network for Bone Age Assessment","display_name":"CFJLNet: Coarse and Fine Feature Joint Learning Network for Bone Age Assessment","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4287890640","doi":"https://doi.org/10.1109/tim.2022.3193711"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2022.3193711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3193711","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Instrumentation and Measurement","raw_type":"journal-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/A5066988252","display_name":"Xiaohua Wang","orcid":"https://orcid.org/0000-0003-1751-2291"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaohua Wang","raw_affiliation_strings":["Laboratory of Knowledge Engineering With Big Data, Ministry of Education, and the Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Laboratory of Knowledge Engineering With Big Data, Ministry of Education, and the Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079096160","display_name":"Wei Fan","orcid":"https://orcid.org/0000-0002-9803-7797"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Fan","raw_affiliation_strings":["Laboratory of Knowledge Engineering With Big Data, Ministry of Education, and the Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Laboratory of Knowledge Engineering With Big Data, Ministry of Education, and the Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091586702","display_name":"Min Hu","orcid":"https://orcid.org/0000-0003-2122-0240"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Hu","raw_affiliation_strings":["Laboratory of Knowledge Engineering With Big Data, Ministry of Education, and the Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Laboratory of Knowledge Engineering With Big Data, Ministry of Education, and the Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021887377","display_name":"Yuhang Wang","orcid":"https://orcid.org/0000-0003-0440-4718"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhang Wang","raw_affiliation_strings":["Laboratory of Knowledge Engineering With Big Data, Ministry of Education, and the Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Laboratory of Knowledge Engineering With Big Data, Ministry of Education, and the Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071943346","display_name":"Fuji Ren","orcid":"https://orcid.org/0000-0003-4860-9184"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuji Ren","raw_affiliation_strings":["School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5066988252"],"corresponding_institution_ids":["https://openalex.org/I16365422"],"apc_list":null,"apc_paid":null,"fwci":4.4873,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.94120769,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"71","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10992","display_name":"Forensic Anthropology and Bioarchaeology Studies","score":0.9988999962806702,"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":0.9988999962806702,"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":0.998199999332428,"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":0.9803000092506409,"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/discriminative-model","display_name":"Discriminative model","score":0.8450469970703125},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7090139985084534},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6644625067710876},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.6524226665496826},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6509006023406982},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5659988522529602},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5581786036491394},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.538021445274353},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5317256450653076},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5117411613464355},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4552350342273712},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.44349968433380127},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4243125319480896},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13192540407180786},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08850258588790894}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8450469970703125},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7090139985084534},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6644625067710876},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.6524226665496826},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6509006023406982},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5659988522529602},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5581786036491394},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.538021445274353},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5317256450653076},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5117411613464355},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4552350342273712},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.44349968433380127},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4243125319480896},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13192540407180786},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08850258588790894},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2022.3193711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3193711","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G2099074206","display_name":null,"funder_award_id":"PA2021GDSK0093","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G7335566223","display_name":null,"funder_award_id":"PA2022GDSK0065","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8137922356","display_name":null,"funder_award_id":"62176084","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1485009520","https://openalex.org/W1971568952","https://openalex.org/W1975572110","https://openalex.org/W2104657103","https://openalex.org/W2171827933","https://openalex.org/W2183341477","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2202499615","https://openalex.org/W2330485005","https://openalex.org/W2344641332","https://openalex.org/W2345010043","https://openalex.org/W2440214111","https://openalex.org/W2530289846","https://openalex.org/W2592232824","https://openalex.org/W2773607772","https://openalex.org/W2798706078","https://openalex.org/W2808062989","https://openalex.org/W2883298022","https://openalex.org/W2891951760","https://openalex.org/W2903408278","https://openalex.org/W2918321871","https://openalex.org/W2951934944","https://openalex.org/W2962992847","https://openalex.org/W2963066927","https://openalex.org/W2979871943","https://openalex.org/W2980027842","https://openalex.org/W2986821660","https://openalex.org/W2989916101","https://openalex.org/W2996870993","https://openalex.org/W3022033765","https://openalex.org/W3097760447","https://openalex.org/W3103400039","https://openalex.org/W3106250896","https://openalex.org/W3128907596","https://openalex.org/W3130788242","https://openalex.org/W3131296864","https://openalex.org/W3180883433","https://openalex.org/W3200944276","https://openalex.org/W3206155853","https://openalex.org/W3215315116","https://openalex.org/W4206655927","https://openalex.org/W4210255734","https://openalex.org/W4213421704","https://openalex.org/W4221042498","https://openalex.org/W4285111337","https://openalex.org/W4288622677","https://openalex.org/W6759000249","https://openalex.org/W6790324524"],"related_works":["https://openalex.org/W2118717649","https://openalex.org/W2413243053","https://openalex.org/W410723623","https://openalex.org/W3208297503","https://openalex.org/W3119773509","https://openalex.org/W2889153461","https://openalex.org/W2964117661","https://openalex.org/W4388405611","https://openalex.org/W2619127353","https://openalex.org/W4309346246"],"abstract_inverted_index":{"Effectively":[0],"locating":[1],"fine":[2,8,47,71,119,138,149],"discriminative":[3,90],"regions":[4,48,146,155],"and":[5,25,46,49,59,69,92,112,171,177,211],"fully":[6,50,109],"analyzing":[7],"region":[9],"features":[10,33,52],"is":[11],"a":[12,57,67,70,95,185],"challenging":[13],"task":[14],"in":[15,40,74,106,125,174],"bone":[16],"age":[17],"assessment":[18],"(BAA).":[19],"Existing":[20],"annotation-based":[21],"methods":[22,27],"are":[23,151,205],"labor-intensive":[24],"attention-based":[26],"can":[28,102],"only":[29],"learn":[30,51],"semantic":[31],"global":[32],"from":[34],"coarse":[35,45,68,131],"regions.":[36],"In":[37,140],"this":[38],"paper,":[39],"order":[41],"to":[42,88,129,133],"efficiently":[43],"locate":[44,89],"of":[53,76,80,118,137,156,168,189,200],"them,":[54],"we":[55,83,121],"present":[56],"&#x201C;Coarse":[58],"Fine":[60],"Feature":[61,97],"Joint":[62],"Learning":[63],"Network&#x201D;":[64],"(CFJLNet,":[65],"including":[66],"branch).":[72],"Specifically,":[73],"each":[75],"the":[77,81,135,142,154,166,169,193,198,201],"two":[78,208],"branches":[79],"CFJLNet,":[82],"first":[84],"obtain":[85],"attentions":[86,107,111,132,150],"used":[87,159],"regions,":[91,120],"then":[93],"design":[94,122],"&#x201C;Dual":[96],"Fusion&#x201D;":[98],"(DFF)":[99],"module":[100,128],"that":[101,145],"capture":[103],"long-term":[104],"dependencies":[105],"while":[108],"fuse":[110],"features.":[113],"Furthermore,":[114],"for":[115],"accurate":[116],"localization":[117],"an":[123],"&#x201C;Attention":[124],"Attention&#x201D;":[126],"(<i>A</i><sup>2</sup>)":[127],"force":[130],"guide":[134],"generation":[136],"attentions.":[139],"particular,":[141],"visualization":[143],"show":[144],"located":[147],"by":[148,160],"consistent":[152],"with":[153],"interest":[157],"(ROIs)":[158],"TW3":[161],"method.":[162],"We":[163],"empirically":[164],"analyze":[165],"contributions":[167],"DFF":[170],"<i>A</i><sup>2</sup>":[172],"modules":[173],"our":[175],"network":[176],"demonstrate":[178],"their":[179],"superiority.":[180],"The":[181],"experimental":[182],"results":[183],"showed":[184],"mean":[186],"absolute":[187],"error":[188],"4.07":[190],"months":[191],"on":[192,207],"RSNA":[194],"dataset.":[195],"To":[196],"validate":[197],"generalizability":[199],"proposed":[202],"network,":[203],"experiments":[204],"conducted":[206],"face":[209],"datasets,":[210],"it":[212],"also":[213],"achieves":[214],"excellent":[215],"performance.":[216]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}