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) tomogr aphy using noisy projections. A wavelet decomposition down to the coar sest level is done on the noisy signal. The signal at various levels i s estimated using a Wiener filter. By assuming that the projections ar e 1/f processes, the Wiener filtering reduces to a scalar multiplicati on. Using the Wiener filter and regularity property of the wavelets, w e combine the estimation and localisation of the noisy projections for ROI imaging. Experimental results are shown on Shepp-Logan phantom an d actual CT images. The validity of the 1/f model for projections of r eal life images is also shown.