1. A method of bone registration of quantitative computed tomography (CT) images, comprising acquiring data of a baseline CT scan and a follow-up CT scan of a bone in an individual to produce a baseline image and a follow-up image, segmenting bony structures of the baseline image and the follow-up image, respectively, via an approach that can determine thresholds for separating the bony structure from background and non-skeletal tissues, wherein said approach is a double-clustering approach including: performing a first K-means clustering on intensities of voxels in each image to separate a foreground from a background, wherein K=2 in said first K-means clustering and the cluster with higher average intensity is considered to be the foreground, applying a second K-means clustering on intensities of voxels in foreground regions of each image, wherein K=2 in said second K-means clustering, whereby non-bone structures are removed and clusters with higher average intensity are determined to be bony regions, and optionally identifying cortical bone from a segmented bone region as a largest connected component in volume data, and registering a bone surface of the follow-up image with a bone surface in the baseline image using a 3D registration algorithm, whereby an overlap of the follow-up bone surface and the baseline bone surface is better than that before the registration, wherein, the follow-up bone surface and the baseline bone surface are aligned.