X-ray computed tomography (XCT) is a powerful non-invasive imaging tool for biomedical applications. It provides not only morphology but also the absolute value of the linear attenuation coefficient distribution of the specimen in three dimensions, which is helpful in osteoporosis and other component-sensitive studies. Spatial resolution and specimen size are coupled through the detector's field of view (FOV) and the number of elements in the area detector. When the FOV is smaller than the specimen size, the truncated-data problem arises, which can cause large errors in the values of the volume elements (voxels) in the reconstruction. Zoom-in tomography is a technique that images a small region of interest (ROI) in a large-size specimen with high resolution and uses low-resolution data for the entire specimen to reduce reconstruction errors in the ROI. We developed a method to estimate the residual error in linear attenuation coefficient values persisting in zoom-in tomography and used it to judge the accuracy of zoom-in tomographic reconstructions. In this work, we imaged a sample of trabecular bone with zoom-in tomography and quantified differences in voxel values, concentrating on comparisons of low and high mineral regions of the bone.
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