Application of anisotropic diffusion potential to sparse view reconstruction problem

In this work, a new constrained optimization problem associated with anisotropic diffusion potential was formulated to provide reconstructions from projection data acquired from limited number of view angles. Our results from both simulated data and physical phantom data showed that the anisotropic diffusion method can produce appealing images from sparse view data which suggests it could be potentially applied to lower the dose delivered to patient. Compared with the total variation minimization algorithm, the anisotropic diffusion method can be an alternative candidate to sparse view reconstruction problem. The similarities between anisotropic diffusion and TV based algorithms are also discussed. A possible combination of the anisotropic diffusion and total variation methods is suggested in this paper.