Proof-of-concept comparison of an artificial intelligence-based bone age assessment tool with Greulich-Pyle and Tanner-Whitehouse version 2 methods in a pediatric cohort

Milner GR, Levick RK, Kay R (1986) Assessment of bone age: a comparison of the Greulich and Pyle, and the Tanner and Whitehouse methods. Clin Radiol 37:119–121

Article  CAS  PubMed  Google Scholar 

Schmeling A, Dettmeyer R, Rudolf E, Vieth V, Geserick G (2016) Forensic age estimation. Dtsch Arztebl Int 113:44–50

PubMed  PubMed Central  Google Scholar 

Alshamrani K, Offiah AC (2020) Applicability of two commonly used bone age assessment methods to 21st-century UK children. Eur Radiol 30:504–513

Article  PubMed  Google Scholar 

Murthy V, Begum A, Kumar P, Lalitha C (2013) Reliability of an objective method of evaluating skeletal maturity based on cervical vertebral bone age as compared with the TW2 method. J Indian Orthod Soc 47:202–206

Article  Google Scholar 

Halabi SS, Prevedello LM, Kalpathy-Cramer J et al (2019) The RSNA pediatric bone age machine learning challenge. Radiology 290:498–503

Article  PubMed  Google Scholar 

Lee H, Tajmir S, Lee J, Zissen M, Yeshiwas BA, Alkasab TK, Choy G, Do S (2017) Fully automated deep learning system for bone age assessment. J Digit Imaging 30:427–441

Article  PubMed  PubMed Central  Google Scholar 

Radiological Society of North America. RSNA AI Challenge – Bone Age 2017. Available from: https://www.rsna.org/en/education/ai-resources-and-training/ai-challenges. Accessed August 2025.

Gräfe D, Beeskow AB, Pfäffle R, Rosolowski M, Chung TS, DiFranco MD (2024) Automated bone age assessment in a German pediatric cohort: agreement between an artificial intelligence software and the manual Greulich and Pyle method. Eur Radiol 34:4407–4413

Article  PubMed  Google Scholar 

Boitsios G, De Leucio A, Preziosi M, Seidel L, Aparisi Gómez MP, Simoni P (2021) Are automated and visual Greulich and Pyle-based methods applicable to Caucasian European children with a Moroccan ethnic origin when assessing bone age? Cureus 13:e13478

PubMed  PubMed Central  Google Scholar 

Koçak B, Durmaz EŞ, Ateş E, Kılıçkesmez Ö (2019) Radiomics with artificial intelligence: a practical guide for beginners. Diagn Interv Radiol 25:485–495

Article  PubMed  PubMed Central  Google Scholar 

Booz C, Yel I, Wichmann JL, Boettger S, Al Kamali A, Albrecht MH, Martin SS et al (2020) Artificial intelligence in bone age assessment: accuracy and efficiency of a novel fully automated algorithm compared to the Greulich-Pyle method. Eur Radiol Exp 4:6

Article  PubMed  PubMed Central  Google Scholar 

Larson DB, Chen MC, Lungren MP, Halabi SS, Stence NV, Langlotz CP (2018) Performance of a deep-learning neural network model in assessing skeletal maturity on pediatric hand radiographs. Radiology 287:313–322

Article  PubMed  Google Scholar 

Santomartino SM, Putman K, Beheshtian E, Parekh VS, Yi PH (2024) Evaluating the robustness of a deep learning bone age algorithm to clinical image variation using computational stress testing. Radiology: Artificial Intelligence 6:e230240

PubMed  PubMed Central  Google Scholar 

Pape J, Rosolowski M, Pfäffle R, Beeskow AB, Gräfe D (2025) A critical comparative study of the performance of three AI-assisted programs for bone age determination. Eur Radiol 35:1190–1196

Article  PubMed  Google Scholar 

Bull RK, Edwards PD, Kemp PM, Fry S, Hughes IA (1999) Bone age assessment: a large scale comparison of the Greulich and Pyle, and Tanner and Whitehouse (TW2) methods. Arch Dis Child 81:172–173

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ontell FK, Ivanovic M, Ablin DS, Barlow TW (1996) Bone age in children of diverse ethnicity. AJR Am J Roentgenol 167:1395–1398

Article  CAS  PubMed  Google Scholar 

Mora S, Boechat MI, Pietka E, Huang HK, Gilsanz V (2001) Skeletal age determinations in children of European and African descent: applicability of the Greulich and Pyle standards. Pediatr Res 50:624–628

Article  CAS  PubMed  Google Scholar 

Martín Pérez IM, Martín Pérez SE, Vega González JM, Molina Suárez R, García Hernández AM, Rodríguez Hernández F et al (2024) Validation of the Greulich and Pyle atlas for radiological bone age assessments in a pediatric population from the Canary Islands. Healthcare (Basel) 12:1847

Article  PubMed  Google Scholar 

Hashim HA, Mansoor H, Mohamed MHH (2018) Assessment of skeletal age using hand-wrist radiographs following Bjork system. J Int Soc Prev Community Dent 8:482–487

Article  PubMed  PubMed Central  Google Scholar 

Shelmerdine SC, White RD, Liu H, Arthurs OJ, Sebire NJ (2022) Artificial intelligence for radiological paediatric fracture assessment: a systematic review. Insights Imaging 13:94

Article  PubMed  PubMed Central  Google Scholar 

Laborie LB, Naidoo J, Pace E, Ciet P, Eade C, Wagner MW, Huisman TAGM et al (2023) European society of paediatric radiology artificial intelligence taskforce: a new taskforce for the digital age. Pediatr Radiol 53:576–580

Article  PubMed  Google Scholar 

Comments (0)

No login
gif