A preliminary investigation of image reconstruction with variable resolutions in diagnostic CT

For certain applications in tomographic imaging, precise knowledge of the image within a regions of interest (ROI) is often desired, while rough knowledge outside the ROI is sufficient. Conventional iterative algorithms can only yield image values on uniform grids. It is of practical merit to develop iterative algorithms for image reconstruction with variable resolutions - a high-resolution ROI image and a coarse image outside the ROI. In this work, we investigate optimization-based algorithms for image reconstruction with variable spatial resolutions. We apply the modified algorithms to real cadaver data acquired with a Toshiba diagnostic CT scanner. The results of our study show that optimization-based algorithms can be developed for yielding image reconstruction on grids with variable resolutions. This work may also have implications for lowering computation load.