An effective methodology for identification of bone related diseases using bivariate gaussian mixture model

Abstract

Medical imaging deals with the analysis of medical data and helps to have more complete study regarding the diseases. Among the various diseases attributed to human anatomy, bone fracture is one such complication which needs to be diagnosed appropriately. This article formulates a methodology for the identification of bone fracture more appropriately such that effective treatment can be imparted. The works are carried out on benchmark dataset and the results showcase accuracy of around 95%.