Journal papers, co-authored by Visiana or Tübingen University
(these can also be found by this PubMed search)
[1] Thodberg HH, Kreiborg S, Juul A, Pedersen KD: The BoneXpert Method for Automated Determination of Skeletal Maturity, IEEE Trans Medical Imaging, Vol. 28 (1), pp 52-66 (2009), abstract. (A pdf for personal use can be obtained by sending an email to )
[2] van Rijn R, Lequin MH, Thodberg HH: Automatic Determination of Greulich and Pyle bone age in healthy Dutch children, Pediatric Radiology Vol. 39 (6) pp 591-7 (2009), pdf (open access), Figure 1 in good quality
[3] Martin DD, Deusch D, Schweizer R, Binder G, Thodberg HH, Ranke MB: Clinical application of automatic Greulich-Pyle bone age in children with short stature, Pediatric Radiology Vol 39 (6) pp 598-607 (2009), abstract.
[4] Martin DD, Sato K, Sato M, Thodberg HH, Tanaka T: Validation of a new method for automated determination of bone age in Japanese children, Horm. Res. Paediatr. Vol. 73(5), pp 398-404, (2010) abstract
[5] Thodberg HH, van Rijn R, Tanaka T, Martin DD, Kreiborg S: A paediatric bone index derived by automated radiogrammetry, Osteoporosis International Vol. 21 (8), pp 1391-1400 (2009) (full text open access)
[6] Martin DD, Neuhof J, Jenni OG, Ranke MB, Thodberg HH: Automatic Determination of Left- and Right-Hand Bone Age in the First Zurich Longitudinal Study. Horm. Res. Paediatr. Vol. 74 (1) pp. 50-55 (2010) abstract
[7] Thodberg HH, Neuhof J, Ranke MB, Jenni OG, Martin DD: Validation of Bone Age Methods by Their Ability to Predict Adult Height. Horm. Res. Paediatr. Vol. 73 (6), pp 398-404 (2010) abstract
[8] Thodberg HH, Jenni OG, Ranke MB, Martin DD: Standardization of the Tanner-Whitehouse bone age method in the context of automated image analysis, Ann Hum Biol. Vol. 39(1) pp 68-75 (2012), abstract
[9] Thodberg HH, Sävendahl L: Validation and Reference Values of Automated Bone Age Determination for Four Ethnicities. Acad. Radiol. Vol. 17 (11), pp1425-32 (2010), abstract
[10] Thodberg HH: Clinical review: An automated method for determination of bone age, J. Clin. Endocrinol. Metab. Vol. 94 (7), pp 2239-44, (2009), abstract (as well as full text pdf freely available)
[11] Thodberg HH, Jenni OG, Caflisch J, Ranke MB, Martin DD: Prediction of Adult Height Based on Automated Determination of Bone Age, J. Clin. Endocrinol. Metab. Vol. 94 (12), pp 4868-74 (2009), abstract and full text pdf freely available here
[12] Martin DD, Heckmann C, Jenni OG, Ranke MB, Binder G, Thodberg HH: Metacarpal thickness, width, length and medullary diameter in children--reference curves from the First Zürich Longitudinal Study, Osteoporosis International Vol 22 (5), pp 1525-36 (2011), abstract
[13] Zhang SY, Liu G, Ma CG, Han YS, Shen XZ, Xu RL, Thodberg HH: Automated Determination of Bone Age in a Modern Chinese Population. ISRN Radiology, Volume 2013 (2013) full paper freely available here.
[14] Martin DD, Meister K, Schweizer R, Ranke MB, Thodberg HH, Binder G: Validation of automatic bone age rating in children with precocious and early puberty, J Pediatr Endocrinol Metab. Vol. 24 (11-12) pp 1009-14 (2011), abstract
[15] Unrath M, Thodberg HH, Schweizer R, Ranke MB, Binder G, Martin DD: Automation of bone age reading and a new prediction method improve adult height prediction in children with short stature. Horm. Res. Paediatr. Vol. 78, pp 312-319 (2012) abstract
[16] van Rijn RR, Thodberg HH: Bone age assessment: automated techniques coming of age? Acta Radiol. Vol 54, p 1024-9 (2013) abstract
[17] Martin DD, Heil K, Heckmann C, Zierl A, Schaefer J, Ranke NB and Binder G: Validation of automatic bone age determination in children with congenital adrenal hyperplasia, Pediatric Radiology, Vol. 43, p 1615-21 (2013). abstract
[19] Martin DD, Schittenhelm J, Thodberg HH: Validation of adult height prediction based on automated bone age determination in the Paris Longitudinal Study of healthy children. Pediatr Radiol. 46, pp 263-9 (2016) abstract
[21] Thodberg HH, Böttcher J, Lomholt J, Kreiborg S, Wolf G, Pfeil A: A new implementation of digital X-ray radiogrammetry and reference curves of four indices of cortical bone for healthy European adults. Archives of Osteoporosis., doi: 10.1007/s11657-016-0267-2. Epub Apr 26 (2016) abstract
[22] Halabi, Safwan S., Luciano M. Prevedello, Jayashree Kalpathy-Cramer, Artem B. Mamonov, Alexander Bilbily, Mark Cicero, Ian Pan et al. The RSNA pediatric bone age machine learning challenge." Radiology 290, no. 2 (2018): 498-503. Appendix with conditions, terms and winners
[23] Thodberg HH, van Rijn RR, Jenni OG, Martin DD. Automated determination of bone age from hand X-rays at the end of puberty and its applicability for age estimation. Int J Leg Med. (2016); abstract
[24] Thodberg HH, Thodberg B, Ahlkvist J, Offiah AC. Autonomous artificial intelligence in pediatric radiology: the use and perception of BoneXpert for bone age assessment. Pediatric Radiology (2022). Open Access
[25] Martin DD, Calder AD, Ranke MB, Binder G, Thodberg HH. Accuracy and self-validation of automated bone age determination. Scientific Reports 12, Article number 6388 (2022). Open Access Supplementary material as PDF
Journal papers, not co-authored by Visiana or Tübingen University
[a] Nüsken E, Imschinetzki D, Nüsken KD, et al: Automated Greulich-Pyle bone age determination in children with chronic kidney disease. Pediatr Nephrol. 30, pp 1173-9 (2015) abstract
[b] Wang YM, Tsai TH, Hsu JS, Chao MF, Wang YT, Jaw TS: Automatic assessment of bone age in Taiwanese children: A comparison of the Greulich and Pyle method and the Tanner and Whitehouse 3 method. Kaohsiung J Med Sci. Vol. 36 (11), pp 937-943 (2020), Open access
[c] Uday, S., Manaseki-Holland, S., Bowie, J. et al: The effect of vitamin D supplementation and nutritional intake on skeletal maturity and bone health in socio-economically deprived children. Eur J Nutr 60, pp 3343–3353 (2021), Open access
[d] Shalof H, Dimitri P, Shuweihdi F, Offiah AC: Which skeletal imaging modality is best for assessing bone health in children and young adults compared to DXA? A systematic review and meta-analysis. Bone. 150: 116013. (2021) Abstract
[e] Vogiatzi MG, Davis SM, Ross JL: Cortical Bone Mass is Low in Boys with Klinefelter Syndrome and Improves with Oxandrolone. J Endocr Soc. 10;5 (4) (2021) Abstract
[f] za C, Khadilkar AV, Mondkar S, Gondhalekar K. et al: A comparison of bone age assessments using automated and manual methods in children of Indian ethnicity. Pediatr Radiol. 52 (11): pp 2188-2196, (2022) Abstract
[g] Oza C, Khadilkar AV, Mondkar S, Gondhalekar K, Ladkat A, et al: A comparison of bone age assessments using automated and manual methods in children of Indian ethnicity. Pediatr Radiol. 52 (11), pp 2188-2196, (2022) Abstract
[h] Alaimo, D., Terranova, M.C., Palizzolo, E. et al.: Performance of two different artificial intelligence (AI) methods for assessing carpal bone age compared to the standard Greulich and Pyle method. La Radiologia Medica, Springer (2024) Open access
[i] van Leeuwen KG, Schalekamp S, Rutten MJCM, Huisman M. et al: Comparison of Commercial AI Software Performance for Radiograph Lung Nodule Detection and Bone Age Prediction. Radiology, Vol 310 (1), (2024) Open access
Book chapter
Thodberg HH, Juul A, Lomholt J, Martin DD, Jenni OG, Caflisch J, Ranke MB, Kreiborg S: Adult Height Prediction Models, in Handbook of Growth and Growth Monitoring in Health and Disease, Preedy R (ed.), Springer (2012) abstract, (the original manuscript as pdf, copyrighted material; permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the publisher)
Relevant conference abstracts
[I] DD Martin, C Heckmann, MB Ranke, G Binder, HH Thodberg,Differentiation of GH effects on metacarpal bone in children with GHD, ICCBH5, Cambridge, UK. June 23-26, 2009 Bone, Volume 45, Page S60
[I] Shao-Yan Zhang, Toshiaki Tanaka, David D Martin et al: Adult height prediction for han children based on automated bone age determination, ESPE 2012, Glasgow, Hormone Research in Pediatrics
[III] HH Thodberg, SY Zhang: Reference curves for Bone Health Index for Han children from five large cities in China, and a comparison to Asian-American children, ICCBH 2013, Rotterdam, Bone Abstracts
[IV] HH Thodberg, D Martin, J Caflisch, O Jenni: Bone Health: Swiss Children have less in the bank than a generation ago, ICCBH 2013, Rotterdam, Bone Abstracts
[V] DD Martin, J Pettifor, HH Thodberg: At last, an adult height prediction model for black children, ESPE/PES Joint conference 2013, Milan, Hormone Research in Pediatrics
[VI] HH Thodberg, M Bardsley, A Gosek, J Ross: How precisely can we measure increments of bone age and Bone Health Index with an automated method in boys with Klinefelter syndrome? ESPE-2014 Dublin, Hormone Research in Pediatrics, poster
[VII] DD Martin, S Mortensen, O Jenni, HH Thodberg: Making adult height prediction complete: Forecasting the age of the growth spurt and the height & velocity trajectories until adulthood, ESPE-2015 Barcelona, Hormone Research in Pediatrics, poster
[VIII] HH Thodberg, P Thrane, DD Martin: Reference values of cortical thickness, bone width, and Bone Health Index in metacarpals of children from age 0 y, as determined with an extension of the fully automated BoneXpert bone age method, ICCBH 2019, Salzburg, poster
[IX] DD Martin, HH Thodberg, Validation of a new version of BoneXpert bone age in children with congenital adrenal hyperplasia (CAH), precocious puberty (PP), growth hormone deficiency (GHD), Turner syndrome (TS), and other short stature diagnoses, ESPE-2019, Vienna, abstract. All abstracts from ESPE-2019 are here.
[X] HH Thodberg, P Thrane, DD Martin, A Liliana: Reference curves for Bone Health Index in twelve populations, representing five ethnicities across four continents, ICCBH 2024, Salzburg, poster
Other publications on technology relevant to BoneXpert
[A] A. Rosholm, L. Hyldstrup, L. Baeksgaard, M. Grunkin, and H. H. Thodberg, Estimation of Bone Mineral Density by Digital X-ray Radiogrammetry: Theoretical Background and Clinical Testing, Osteoporosis International, vol. 12, no. 11, pp. 961-969, 2001 (abstract)
[B] H. H. Thodberg, Hands-on experience with active appearance models, Proceedings of SPIE (Medical Imaging 2002, Image Processing), vol. 4684, pp. 495-506, 2002 (pdf of full text)
[C] H. H. Thodberg and A. Rosholm, Application of the active shape model in a commercial medical device for bone densitometry, Image and Vision Computing, vol. 21, no. 13-14, pp. 1155-1161, 2003. (This appeared initially as a contribution to the British Machine Vision Conference 2001 (where it won an award), and the full text of this version is available as pdf)
[D] H. H. Thodberg, Minimum Description Length shape and appearance models, Proceedings of Information Processing in Medical Imaging, vol. 18, pp. 51-62, 2003.(abstract at Springer, pdf of full text)
[E] H. H. Thodberg and H. Olafsdottir, Adding curvature to minimum description length shape models, Proceedings of British Machine Vision Conference, vol. 2, pp. 251-260, 2003 (pdf) (You can download the Matlab code of the method presented in this, and the preceding paper in this zip file)