{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T21:04:53Z","timestamp":1769202293627,"version":"3.49.0"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2018,10,15]],"date-time":"2018-10-15T00:00:00Z","timestamp":1539561600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Digit Imaging"],"published-print":{"date-parts":[[2019,4]]},"DOI":"10.1007\/s10278-018-0135-2","type":"journal-article","created":{"date-parts":[[2018,10,15]],"date-time":"2018-10-15T11:15:21Z","timestamp":1539602121000},"page":"283-289","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Accurate Age Determination for Adolescents Using Magnetic Resonance Imaging of the Hand and Wrist with an Artificial Neural Network-Based Approach"],"prefix":"10.1007","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6530-7730","authenticated-orcid":false,"given":"Fuk Hay","family":"Tang","sequence":"first","affiliation":[]},{"given":"Jasmine L.C.","family":"Chan","sequence":"additional","affiliation":[]},{"given":"Bill K.L.","family":"Chan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,10,15]]},"reference":[{"key":"135_CR1","doi-asserted-by":"publisher","unstructured":"Tscholl PM, Junge A, Dvorak J, Zubler V. MRI of the wrist is not recommended for age determination in female football players of U-16\/U-17 competitions. Scand J Med Sci Sports. 2016 Mar;26(3):324\u20138. \n                    https:\/\/doi.org\/10.1111\/sms.12461\n                    \n                  . Epub 2015 Apr 16.","DOI":"10.1111\/sms.12461"},{"key":"135_CR2","doi-asserted-by":"crossref","unstructured":"Sarkodie BD, Ofori EK, Pambo P. MRI to determine the chronological age of Ghanaian footballers. The South African Journal of Sports Medicine, Vol 25, No 3 (2013)","DOI":"10.17159\/2078-516X\/2013\/v25i3a359"},{"key":"135_CR3","doi-asserted-by":"crossref","unstructured":"Schmeling A, Geserick G, Reisinger W, Olze A: Age estimation. Forensic Sci Int. 165(2\u20133):178\u2013181, 2007 Jan 17 Epub 2006 Jun 19","DOI":"10.1016\/j.forsciint.2006.05.016"},{"issue":"2","key":"135_CR4","doi-asserted-by":"publisher","first-page":"808","DOI":"10.1016\/j.ridd.2010.10.019","volume":"32","author":"P Diz","year":"2011","unstructured":"Diz P, Limeres J, Salgado AF, Tom\u00e1s I, Delgado LF, V\u00e1zquez E, Feijoo JF: Correlation between dental maturation and chronological age in patients with cerebral palsy, mental retardation, and Down syndrome. Res Dev Disabil. 32(2):808\u2013817, 2011","journal-title":"Res Dev Disabil."},{"key":"135_CR5","first-page":"211","volume":"30","author":"AM Mughal","year":"2013","unstructured":"Mughal AM, Hassan N, Ahmed A: Bone age assessment methods: A critical review. Pak J Med Sci 30:211\u2013215, 2013","journal-title":"Pak J Med Sci"},{"key":"135_CR6","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1136\/bjsm.2006.031021","volume":"41","author":"J Dvorak","year":"2007","unstructured":"Dvorak J, George J, Junge A, Hodler J: Age determination by magnetic resonance imaging of the wrist in adolescent male football players. Br J Sports Med 41:45\u201352, 2007","journal-title":"Br J Sports Med"},{"key":"135_CR7","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1136\/bjsm.2010.074948","volume":"46","author":"J George","year":"2012","unstructured":"George J, Nagendran J, Azmi K: Comparison study of growth plate fusion using MRI versus plain radiographs as used in age determination for exclusion of overaged football players. Br J Sports Med 46:273\u2013278, 2012","journal-title":"Br J Sports Med"},{"key":"135_CR8","doi-asserted-by":"publisher","first-page":"1697","DOI":"10.1002\/mrm.24439","volume":"69","author":"Y Terada","year":"2013","unstructured":"Terada Y, Kono S, Tamada D, Uchiumi T, Kose K, Miyagi R, Yamabe E, Yoshioka H: Skeletal age assessment in children using an open compact MRI system. Magn Reson Med 69:1697\u20131702, 2013","journal-title":"Magn Reson Med"},{"key":"135_CR9","doi-asserted-by":"publisher","first-page":"1198","DOI":"10.1002\/jmri.24286","volume":"39","author":"E Tomei","year":"2014","unstructured":"Tomei E, Sartori A, Nissman D, al Ansari N, Battisti S, Rubini A, Stagnitti A, Martino M, Marini M, Barbato E, Semelka RC: Value of MRI of the hand and the wrist in evaluation of bone age: Preliminary results. J Magn Reson Imaging 39:1198\u20131205, 2014","journal-title":"J Magn Reson Imaging"},{"key":"135_CR10","unstructured":"Wikipedia: Artificial neural network. Retreived 15 December, 2017 from \n                    https:\/\/en.wikipedia.org\/wiki\/Artificial_neural_network\n                    \n                  ."},{"key":"135_CR11","doi-asserted-by":"crossref","unstructured":"Larson DB, Chen MC, Lungren MP, Halabi SS, Stence NV, Langlotz CP. Performance of a Deep-Learning Neural Network Model in Assessing Skeletal Maturity on Pediatric Hand Radiographs. Radiology Npv 2017.(ahead of print)","DOI":"10.1148\/radiol.2017170236"},{"key":"135_CR12","unstructured":"Bocchi L, Ferrara F, Nicoletti I, Valli G. An artificial neural network architecture for skeletal age assessment. In: Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on: IEEE, 2003:I-1077-1080 vol. 1071"},{"key":"135_CR13","doi-asserted-by":"publisher","first-page":"678","DOI":"10.1016\/j.compmedimag.2008.08.005","volume":"32","author":"J Liu","year":"2008","unstructured":"Liu J, Qi J, Liu Z, Ning Q, Luo X: Automatic bone age assessment based on intelligent algorithms and comparison with TW3 method. Comput Med Imaging Graph 32:678\u2013684, 2008","journal-title":"Comput Med Imaging Graph"},{"key":"135_CR14","unstructured":"Pynsent P, Fairbank J, Carr A. Assessment Methodology in Orthopaedics: Butterworth-Heinemann Medical, 1997"},{"key":"135_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1471-2458-8-320","volume":"8","author":"H-K So","year":"2008","unstructured":"So H-K, Nelson EA, Li AM et al.: Secular changes in height, weight and body mass index in Hong Kong children. BMC Public Health 8:1, 2008","journal-title":"BMC Public Health"},{"key":"135_CR16","doi-asserted-by":"publisher","first-page":"1067","DOI":"10.1016\/j.bone.2011.07.041","volume":"49","author":"CM Modlesky","year":"2011","unstructured":"Modlesky CM, Bajaj D, Kirby JT, Mulrooney BM, Rowe DA, Miller F: Sex differences in trabecular bone microarchitecture are not detected in pre and early pubertal children using magnetic resonance imaging. Bone 49:1067\u20131072, 2011","journal-title":"Bone"},{"key":"135_CR17","doi-asserted-by":"publisher","first-page":"215","DOI":"10.2463\/mrms.2013-0098","volume":"13","author":"Y Terada","year":"2014","unstructured":"Terada Y, Kono S, Uchiumi T et al.: Improved reliability in skeletal age assessment using a pediatric hand MR scanner with a 0.3 T permanent magnet. Magn Reson Med Sci 13:215\u2013219, 2014","journal-title":"Magn Reson Med Sci"},{"key":"135_CR18","first-page":"28","volume":"13","author":"JF Griffith","year":"2007","unstructured":"Griffith JF, Cheng JCY, Wong E: Are western skeletal age standards applicable to the Hong Kong Chinese population? A comparison of the Greulich and Pyle method and the Tanner and Whitehouse method. Hong Kong Medical Journal 13:28\u201332, 2007","journal-title":"Hong Kong Medical Journal"},{"key":"135_CR19","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1590\/S1678-77572006000200014","volume":"14","author":"AI Ortega","year":"2006","unstructured":"Ortega AI, Haiter-Neto F, Ambrosano GMB, B\u00f3scolo FN, Almeida SM, Casanova MS: Comparison of TW2 and TW3 skeletal age differences in a Brazilian population. Journal of Applied Oral Science 14:142\u2013146, 2006","journal-title":"Journal of Applied Oral Science"},{"key":"135_CR20","doi-asserted-by":"publisher","first-page":"371","DOI":"10.1136\/adc.2005.090134","volume":"92","author":"ML Ahmed","year":"2007","unstructured":"Ahmed ML, Warner JT: TW2 and TW3 bone ages: Time to change? Arch Dis Child 92:371\u2013372, 2007","journal-title":"Arch Dis Child"},{"key":"135_CR21","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1136\/adc.81.2.172","volume":"81","author":"RK Bull","year":"1999","unstructured":"Bull RK, Edwards PD, Kemp PM, Fry S, Hughes IA: Bone age assessment: A large scale comparison of the Greulich and Pyle, and Tanner and Whitehouse (TW2) methods. Arch Dis Child 81:172\u2013173, 1999","journal-title":"Arch Dis Child"},{"key":"135_CR22","doi-asserted-by":"crossref","unstructured":"Khan K, Elayappen AS. Bone growth estimation using radiology (Greulich\u2013Pyle and Tanner\u2013Whitehouse methods). In: Handbook of Growth and Growth Monitoring in Health and Disease: Springer, 2012:2937\u20132953","DOI":"10.1007\/978-1-4419-1795-9_176"},{"key":"135_CR23","doi-asserted-by":"publisher","first-page":"1225","DOI":"10.1016\/S0895-4356(96)00002-9","volume":"49","author":"JV Tu","year":"1996","unstructured":"Tu JV: Advantages and disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes. J Clin Epidemiol 49:1225\u20131231, 1996","journal-title":"J Clin Epidemiol"},{"issue":"6","key":"135_CR24","doi-asserted-by":"publisher","first-page":"1374","DOI":"10.2214\/AJR.17.18224","volume":"209","author":"JR Kim","year":"2017","unstructured":"Kim JR, Shim WH, Yoon HM, Hong SH, Lee JS, Cho YA, Kim S: Computerized bone age estimation using deep learning based program: Evaluation of the accuracy and efficiency. AJR Am J Roentgenol. 209(6):1374\u20131380, 2017 Dec. \n                    https:\/\/doi.org\/10.2214\/AJR.17.18224","journal-title":"AJR Am J Roentgenol."},{"key":"135_CR25","doi-asserted-by":"publisher","first-page":"989","DOI":"10.1109\/72.329697","volume":"5","author":"MT Hagan","year":"1994","unstructured":"Hagan MT, Menhaj MB: Training feedforward networks with the Marquardt algorithm. Neural Networks, IEEE Transactions on 5:989\u2013993, 1994","journal-title":"Neural Networks, IEEE Transactions on"}],"container-title":["Journal of Digital Imaging"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-018-0135-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10278-018-0135-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-018-0135-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,14]],"date-time":"2019-10-14T19:03:49Z","timestamp":1571079829000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10278-018-0135-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10,15]]},"references-count":25,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2019,4]]}},"alternative-id":["135"],"URL":"https:\/\/doi.org\/10.1007\/s10278-018-0135-2","relation":{},"ISSN":["0897-1889","1618-727X"],"issn-type":[{"value":"0897-1889","type":"print"},{"value":"1618-727X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,10,15]]},"assertion":[{"value":"15 October 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Ethics approval was also obtained from the University Research Ethics Committee.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with Ethical Standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest"}}]}}