Boehler’s Angle Estimations in Calcaneus Bone by Using Artificial Neural Networks

ilhan OTAĞ, Serkan AKKOYUN, Yaşar TAŞTEMUR, Mehmet ÇİMEN
1.902 633


Abstract. Boehler’s angle has a great importance in diagnosis and treatment of calcaneus bones fractures. In this study, Boehler’s angle was estimated by using artificial neural network method. This angle was obtained from 51 well-preserved calcaneus bones which was previously measured in anatomy laboratory at Cumhuriyet University. The data values for estimation belonging to these 51 different calcaneus bones are maximum anteroposterior length, maximum height, cuboidal facet height, body height and load arm length. By using this five different parameters, ANN estimation on Boehler’s angle was performed. It is clearly seen from the results that the method is capable for the estimation.


Boehler's angle, calcaneus bone, morphometry, artificial neural network

Full Text:

PDF (Türkçe)



Rejman M., The elements of modeling leg and monofin movements using a neural network, Acta Bioengineering and Biomechanics, 2006, 8 (1), 53-61.

Kutilek P., Farkasova B., Prediction of lower extremities’ movement by angle-angle diagrams and neural networks, Acta Bioengineering and Biomechanics, 2011, 13 (2), 57- 65.

Kaufman J.J. et al., A neural network approach for bone fracture healing assessment, IEEE Eng. Med. Biol. Mag. 1990, 9(3), 23-30.

Özerdem M.S., Akpolat V., Yapay Sinir Ağları ile Kemik Yoğunluğunun Sınıflandırılması, IEEE 15. Sinyal İşleme ve İletişim Uygulamaları Kurultayı, 2007, Eskişehir.

Haykin S., Neural networks: a comprehensive foundation, 2nd ed, Prentice-Hall, New Jersey, 1999.

Levenberg K.A., Method for the Solution of Certain Non-Linear Problems in Least Squares, Quart. Appl. Math., 1944, 2, 164-168.

Marquardt D., An Algorithm for Least-Squares Estimation of Nonlinear Parameters, SIAM J. Appl. Math., 1963, 11, 431-441.


Igbigni P.S., Mutesasira A.N., Calcaneal angle in Ugandans, Clinical Anatomy, 2003, 16, 328-330.