Our objective in this paper is to estimate spine curvature in DXA scans. To this end we first train a neural network to predict the middle spine curve in the scan, and then use an integral-based method to determine the curvature along the spine curve. We use the curvature to compare to the standard angle scoliosis measure obtained using the DXA Scoliosis Method (DSM). The performance improves over the prior work of Jamaludin et al. 2018. We show that the maximum curvature can be used as a scoring function for ordering the severity of spinal deformation.

翻译：本文旨在利用DXA扫描估计脊柱曲率。为此，我们首先训练神经网络预测扫描图像中的脊柱中线，继而采用基于积分的方法计算该曲线上的曲率。基于计算得到的曲率值，我们将其与采用DXA侧弯测量法（DSM）获得的标准角度侧弯指标进行对比。结果表明，本方法在性能上优于Jamaludin等人2018年的前期工作。我们证实，最大曲率可作为脊柱变形严重程度分级的评分函数。