Osteoporosis Detection Using Deep Learning

Osteoporosis is a bone disorder which occurs due to low bone mass, degradation of bone micro-architecture and high susceptibility to fracture. It is a major health concern across the world, especially in elderly people. Osteoporosis can cause spinal or hip fractures that may lead to socio-economic burden and high morbidity. Therefore, there is a need for the early diagnosis of osteoporosis and predicting the presence of the fracture. We introduce a Convolutional Neural Network model to effectively diagnose osteoporosis in bone radiography data. Automated diagnosis from digital radiographs is very challenging since the scans of healthy and osteoporotic subjects show little or no visual differences. In this paper, we have proposed a model to separate healthy from osteoporotic subjects using high dimensional textural feature representations computed from radiography images. CNN can help us bring the use of structural MRI measurements of bone quality into clinical practice for the detection of Osteoporosis as it gives high accuracy.