ALGEBRAIC RECONSTRUCTION TECHNIQUES CAN BE MADE COMPUTATIONALLY EFFICIENT

Algebraic reconstruction techniques (ART) are iterative procedures for recovering objects from their projections. It is claimed in this paper that by a careful adjustment of the order in which the collected data are accessed during the reconstruction procedure and of the so-called ''relaxation parameters'' that are to be chosen in an algebraic reconstruction technique, ART can produce high-quality reconstructions with excellent computational efficiency. We demonstrate this by showing, on an example based on a particular (but realistic) medical imaging task, that ART can match the performance of the standard EM approach for maximizing likelihood (from the point of view of that particular medical task), but at an order of magnitude less computational cost.