A performance-based features selection for automatic identification of bone X-ray images
Mrityunjaya V. Latte, V. Kumar Swamy, Basavaraj S. Anami · International Journal of Biomedical Engineering and Technology · 2013
This paper presents a performance-based features selection for automatic identification of bone X-ray images using Artificial Neural Network (ANN). Orthopaedicians use imaging technology such as X-ray, computer tomography, magnetic resonance imaging and the like. In this work, we have considered images of different bone types in the human skeleton such as skull, ribs, tibia, femur, foot, hand, ulna, wrist and the humerous using X-ray images. The shape and texture features are selected based upon the identification accuracies. ANN is used for identification. Identification accuracy of different bones using shape, textures, combined shape and texture features are analysed. It is observed that the accuracies for shape, texture and their combination are 52.87%, 32.33% and 95% respectively. The work is useful for orthopaedics practitioners.