Region-of-interest reconstruction from noisy projections using fractal models and Wiener filtering

In this paper, we present a method for region-of-interest (ROI) tomography using noisy projections. A wavelet decomposition down to the coarsest level is done on the noisy signal. The signal at various levels is estimated using a Wiener filter. By assuming that the projections are 1/f processes, the Wiener filtering reduces to a scalar multiplication. Using the Wiener filter and regularity property of the wavelets, we combine the estimation and localisation of the noisy projections for ROI imaging. Experimental results are shown on Shepp-Logan phantom and actual CT images. The validity of the 1/f model for projections of real life images is also shown.