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Tomographic imaging devices, such as PET/SPECT, suffer from their low resolution capabilities and produce images having partial volume error and non- uniform reconstructed resolution across their field of view. This results in quantification errors and hinders the optimum use of these images in diagnostic and therapeutic applications. This writing provides a detailed insight into the tomographic imaging, image reconstruction methods and proposes recovery methods for non-uniform resolution and partial volume errors in Tomographic image reconstruction. Specifically, it details the resolution characteristics of median root based priors and their comparison with the standard quadratic priors and in general discusses their implementation for the recovery of above mentioned errors in reconstructed images for histogram and List-Mode data reconstruction methods. Readers in medical imaging and image reconstruction methods may benefit from this book including an understanding of basic imaging physics and mathematics.