title: On the convergence of generalized simultaneous iterative reconstruction algorithms.
abstract: In this paper, we generalize the widely used simultaneous block iterative reconstruction algorithm and show that it converges, at a linear rate, to a weighted least-squares and weighted minimum-norm reconstruction. Our theoretical result provides a much simpler proof of the convergence properties obtained by Jiang and Wang and covers a much more general class of algorithms. The frequency domain iterative reconstruction algorithm is then introduced as a special application of our theory.
authors.affiliation: Department of Electrical and Computer Engineering, University of Virginia, Charlottesville 22904, USA. jiongwang@virginia.edu
authors.forename: Jiong
authors.initials: J
authors.lastname: Wang
authors.forename: Yibin
authors.initials: Y
authors.lastname: Zheng
mesh_terms: D000465:Algorithms; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity