Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization.
An iterative algorithm, based on recent work in compressive sensing, is developed for volume image reconstruction from a circular cone-beam scan. The algorithm minimizes the total variation (TV) of the image subject to the constraint that the estimated projection data is within a specified tolerance of the available data and that the values of the volume image are non-negative. The constraints are enforced by the use of projection onto convex sets (POCS) and the TV objective is minimized by steepest descent with an adaptive step-size. The algorithm is referred to as adaptive-steepest-descent-POCS (ASD-POCS). It appears to be robust against cone-beam artifacts, and may be particularly useful when the angular range is limited or when the angular sampling rate is low. The ASD-POCS algorithm is tested with the Defrise disk and jaw computerized phantoms. Some comparisons are performed with the POCS and expectation-maximization (EM) algorithms. Although the algorithm is presented in the context of circular cone-beam image reconstruction, it can also be applied to scanning geometries involving other x-ray source trajectories.
Sidky
Emil Y
EY
Department of Radiology MC-2026, University of Chicago, 5841 S. Maryland Ave., Chicago, IL 60637, USA. sidky@uchicago.edu
Pan
Xiaochuan
X
D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D054893:Cone-Beam Computed Tomography / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D015233:Models, Statistical; D008962:Models, Theoretical; D019047:Phantoms, Imaging; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D012984:Software; D015898:Tomography Scanners, X-Ray Computed; D014965:X-Rays