Dynamic angle selection in binary tomography

In this paper, we present an algorithm for the dynamic selection of projection angles in binary tomography. Based on the information present in projections that have already been measured, a new projection angle is computed, which aims to maximize the information gained by adding this projection to the set of measurements. The optimization model used for angle selection is based on a characterization of solutions of the binary reconstruction problem, and a related definition of information gain. From this formal model, an algorithm is obtained by several approximation steps. Results from a series of simulation experiments demonstrate that the proposed angle selection scheme is indeed capable of finding angles for which the reconstructed image is much more accurate than for the standard angle selection scheme.

► We present an algorithm for dynamic angle selection in binary tomography.
► The selected projection angle maximizes the information gain.
► The algorithm uses several approximation steps, to avoid NP-hardness.
► The results show that our algorithm can choose high quality angles.