Image reconstruction from a limited number of projections: detection/estimation of multiple discs with unknown radii

Considers the problem of tomographic image reconstruction from a limited number of noisy projections. Maximum likelihood estimation is used to reconstruct an image of multiple discs with unknown locations and radii. An efficient algorithm is developed to tackle the computation. The algorithm is successfully applied to images containing as many as twelve discs with widely varying radii and with signal-to-noise ratio as low as 0 dB, and the number of projections used is as few as 16. Experimental results show that the approach significantly outperforms the conventional convolution back-projection method