An interactive method based on multi-objective optimization for limited-angle CT reconstruction

Abstract Objective: Limited-angle X-ray computed tomography (CT) is a typical ill-posed inverse problem, leading to artifacts in the reconstructed image due to the incomplete projection data. Most iteration CT reconstruction methods involve optimizing for a single object. This paper explores a multi-objective optimization model and an interactive method based on multi objective optimization to suppress the artifacts of limited-angle CT.
Approach: The model includes two objective functions on dual-domain within data consis tency constraint. In the interactive method, the measure of structural similarity index (SSIM) is regarded as the value function of decision maker (DM) firstly. Secondly, the DM arranges the objective functions of multi-objective optimization model to be optimized according to their absolute improtance. Finally, the SSIM and the Simulate Anneal (SA) method help the DM choose the desirable reconstruction image by improving the SSIM value during the iteration process.
Main results: Simulation and real data experiments demonstrate that the artifacts can be suppressed by the proposed method, and the results were superior to these reconstructed by other three reconstruction methods in preserving the edge structure of the image.
Significance: The proposed interactive method based on multi-objective optimization shows some potential advantages over classical single object optimization methods.