title: Iterative total-variation reconstruction versus weighted filtered-backprojection reconstruction with edge-preserving filtering.
abstract: Iterative image reconstruction with the total-variation (TV) constraint has become an active research area in recent years, especially in x-ray CT and MRI. Based on Green's one-step-late algorithm, this paper develops a transmission noise weighted iterative algorithm with a TV prior. This paper compares the reconstructions from this iterative TV algorithm with reconstructions from our previously developed non-iterative reconstruction method that consists of a noise-weighted filtered backprojection (FBP) reconstruction algorithm and a nonlinear edge-preserving post filtering algorithm. This paper gives a mathematical proof that the noise-weighted FBP provides an optimal solution. The results from both methods are compared using clinical data and computer simulation data. The two methods give comparable image quality, while the non-iterative method has the advantage of requiring much shorter computation times.
authors.affiliation: Department of Radiology, Utah Center for Advanced Imaging Research (UCAIR), University of Utah, Salt Lake City, UT 84108, USA.
authors.forename: Gengsheng L
authors.initials: GL
authors.lastname: Zeng
authors.forename: Ya
authors.initials: Y
authors.lastname: Li
authors.forename: Alex
authors.initials: A
authors.lastname: Zamyatin
mesh_terms: D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D019047:Phantoms, Imaging; D014057:Tomography, X-Ray Computed