Quantitative region-of-interest tomography using variable field of view

In X-ray computed tomography, the task of imaging only a local region of interest (ROI) inside a larger sample is very important. However, without a priori information, this ROI cannot be exactly reconstructed using only the image data limited to the ROI. We propose here an approach of region-of-interest tomography, which reconstructs a ROI within an object from projections of different fields of view acquired on a specific angular sampling scheme in the same tomographic experiment. We present a stable procedure that not only yields high-quality images of the ROI but keeps as well the quantitative contrast on the reconstructed images. In addition, we analyze the minimum number of projections required for ROI tomography from the point of view of the band region of the Radon transform, which confirms this number must be estimated based on the size of the entire object and not only on the size of the ROI.