Implementation of alternating minimization algorithms for fully 3D CT Imaging

Algorithms based on alternating minimization (AM) have recently been derived for computing maximum-likelihood images in transmission CT, incorporating accurate models of the transmission-imaging process. In this work we report the first fully three-dimensional implementation of these algorithms, intended for use with multi-row detector spiral CT systems. The most demanding portions of the computations, the three-dimensional projections and backprojections, are calculated using a precomputed lookup table containing a discretized version of the point-spread function that maps between the measurement and image spaces. This table accounts for the details of the scanner. Simulated multi-row detector data and real data acquired with a Siemens Sensation 16 scanner were used to test the AM algorithm and its implementation. The estimated attenuation coefficients, reconstructed using a mono-energetic version of our AM algorithm, closely match the known coefficients for the cylinder and embedded objects. We are investigating methods for further accelerating these computations by using a combination of techniques that reduce the time required to compute each iteration and that increase the convergence of the loglikelihood from iteration to iteration.