摘要：Machine Learning (ML) techniques have emerged as a viable option for X-ray screening. Fracture detection is a significant part of muscular X-ray image test. Automatic fracture detection for patients in distant regions helps paramedics in making an early determination and starting prompt medical consideration. In this paper we propose a leg and hand bone fracture detection and classification using k-nearest neighbor (KNN), Support Vector Machine (SVM), Artificial Neural Network (ANN), and Convolutional Neural Network (CNN) classifiers. Also the performance comparisons are carried out for four classifiers. The classification accuracy of the proposed model is 98.39%. The result obtained demonstrates that the effectiveness of CNN classifier as compare to other three classifiers. The performance of CNN classifier is superior.
