Deep Learning Model Research for Cortical Bone Separation in Chest CT Spine Imaging

Osteoporosis is a global skeletal disease which will seriously affect the human life. The early diagnosis of osteoporosis by using bone mineral density (BMD) examination can help to decrease the probability of osteoporosis. In the development of computer aided diagnosis, the calculation of BMD can be achieved by deep learning model in CT, without using the specially measuring devices. In this paper, we used a 3D-Unet model to segment the cortical and cancellous bone in the spine and perform quantitative analysis. After that, the three-dimensional visualization of cortical and cancellous bone was reconstructed, and the BMD value and other information were calculated to help doctors to predict the risk of osteoporosis. The expeirmental result shown that the proposed method achieve high performance in segementation and quantization.