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Boehler’s Angle Estimations in Calcaneus Bone by Using Artificial Neural Networks
Author(s) -
İlhan Otağ,
Serkan Akkoyun,
Yaşar Taştemur,
Mehmet Çimen
Publication year - 2015
Publication title -
cumhuriyet science journal
Language(s) - English
Resource type - Journals
ISSN - 1300-1949
DOI - 10.17776/csj.56855
Subject(s) - calcaneus , artificial neural network , artificial bone , computer science , artificial intelligence , geology , biomedical engineering , engineering , paleontology
. 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.

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