Impact of Norm Selections on the Performance of Prior Image Constrained Compressed Sensing (PICCS)

Advances have been made in recent years in computed tomography (CT) as a result of the development and implementation of new iterative reconstruction methods. Prior Image Constrained Compressed Sensing (PICCS) is one such iterative reconstruction method which iteratively minimizes an objective function to approach a target image. To date, published studies have employed the L-1 norm in the minimization of the objective function. In this study, we investigate the use of L-p norms with p > 1 and investigate how image quality depends on the selection of the L-p norm used in the minimization of the objective function.