title: GPU-accelerated regularized iterative reconstruction for few-view cone beam CT.
abstract: OBJECTIVE
  The present work proposes an iterative reconstruction technique designed for x-ray transmission computed tomography (CT). The main objective is to provide a model-based solution to the cone-beam CT reconstruction problem, yielding accurate low-dose images via few-views acquisitions in clinically acceptable time frames.
  
  
  METHODS
  The proposed technique combines a modified ordered subsets convex (OSC) algorithm and the total variation minimization (TV) regularization technique and is called OSC-TV. The number of subsets of each OSC iteration follows a reduction pattern in order to ensure the best performance of the regularization method. Considering the high computational cost of the algorithm, it is implemented on a graphics processing unit, using parallelization to accelerate computations.
  
  
  RESULTS
  The reconstructions were performed on computer-simulated as well as human pelvic cone-beam CT projection data and image quality was assessed. In terms of convergence and image quality, OSC-TV performs well in reconstruction of low-dose cone-beam CT data obtained via a few-view acquisition protocol. It compares favorably to the few-view TV-regularized projections onto convex sets (POCS-TV) algorithm. It also appears to be a viable alternative to full-dataset filtered backprojection. Execution times are of 1-2 min and are compatible with the typical clinical workflow for nonreal-time applications.
  
  
  CONCLUSIONS
  Considering the image quality and execution times, this method may be useful for reconstruction of low-dose clinical acquisitions. It may be of particular benefit to patients who undergo multiple acquisitions by reducing the overall imaging radiation dose and associated risks.
authors.affiliation: Département de physique, de génie physique et d'optique, Université Laval, Québec, Québec G1V 0A6, Canada.
authors.forename: Dmitri
authors.initials: D
authors.lastname: Matenine
authors.affiliation: Département de génie électrique/Institut de génie biomédical, École Polytechnique de Montréal, C.P. 6079, succ. Centre-ville, Montréal, Québec H3C 3A7, Canada.
authors.forename: Yves
authors.initials: Y
authors.lastname: Goussard
authors.affiliation: Département de physique, de génie physique et d'optique and Centre de recherche sur le cancer, Université Laval, Québec, Québec G1V 0A6, Canada.
authors.forename: Philippe
authors.initials: P
authors.lastname: Després
mesh_terms: D000465:Algorithms; D003196:Computer Graphics / Q000295:instrumentation*; D003198:Computer Simulation; D054893:Cone-Beam Computed Tomography / Q000295:instrumentation* / Q000379:methods*; D006257:Head / Q000000981:diagnostic imaging; D006801:Humans; D008962:Models, Theoretical; D010388:Pelvis / Q000000981:diagnostic imaging; D019047:Phantoms, Imaging; D013997:Time Factors; D014965:X-Rays