Osteoporosis is a disease where bone density and structural quality deteriorate, leading to weakness and bone fragility of the skeleton and increase risk of fracture. At present the clinical assessment of osteoporosis relies mainly on X-ray techniques. All these techniques use ionizing radiation and are relatively expensive and bulky. Quantitative ultrasound (QUS) methods for bone assessment are less expensive, faster, simpler and more portable than their X- ray components [1]. Biochemical markers of bone turnover are currently being investigated as a means of assessing bone. In our study, we have developed a reflection technique for prediction of osteoporosis, based on AR2 Autoregression stochastic model. Ultrasonic measurements were performed by immersion with a transmitted/received broadband transducer with a center frequency 3.5MHz. From experimental results, our proposed AR2 Autoregression Stochastic Model correlated with BMD values is better than Biochemical markers method. This study shows the feasibility of our proposed.
