Trajectory Optimization in Computed Tomography Based on Object Geometry

Abstract

We present a new approach for the task of trajectory optimization for X-ray computed tomography (CT) in a robot-based CT (RoboCT) application. An optimized trajectory corresponds to a projection set of predefined size that leads to a 3Dreconstruction with less image-artifacts than other possible sets of the same size. We incorporate prior knowledge through a model of the object and simulated X-ray projections of the interested scenario. We formulate the optimization problem as maximization of an objective function and solve it heuristically by means of a genetic algorithm. As objective function, we use a metric that correlates with the amount of edge information of a projection set, since we assume that this characteristic is important for a reconstruction with low image-artifacts. The metric is based on wavelet analysis of the projections. We carry out computer experiments for a test object made of homogeneous material. The optimized trajectory allows a sharp reconstruction of straight edges and clearly outperforms reconstructions from standard trajectories.