Title :
A fast preconditioned conjugate gradient algorithm for regularized WLS reconstruction for PET
Author :
Chinn, Garry ; Huang, Sung-Cheng
Author_Institution :
Sch. of Med., California Univ., Los Angeles, CA, USA
Abstract :
In this paper, new theory and methods for a class of preconditioners are developed for accelerating the convergence rate of iterative reconstruction. A preconditioned conjugate gradient (PCG) iterative algorithm for weighted least squares reconstruction (WLS) is formulated for emission tomography. A linear regularization method is adopted and shown to be equivalent to penalized WLS reconstruction with quadratic penalty functions. Using simulated positron emission tomography (PET) data of the Hoffman brain phantom, it was shown that the convergence rate of the PCG using the new preconditioner is an order-of-magnitude faster compared to the standard conjugate gradient algorithm. It is also significantly faster than previously proposed preconditioners for emission tomography
Keywords :
algorithm theory; brain; image reconstruction; iterative methods; least mean squares methods; medical image processing; positron emission tomography; Hoffman brain phantom; PET; fast preconditioned conjugate gradient algorithm; iterative reconstruction convergence rate; medical diagnostic imaging; nuclear medicine; preconditioners; quadratic penalty functions; weighted least squares reconstruction; Acceleration; Biomedical imaging; Computational efficiency; Convergence; Equations; Image converters; Image reconstruction; Iterative algorithms; Positron emission tomography; Vectors;
Conference_Titel :
Nuclear Science Symposium and Medical Imaging Conference Record, 1995., 1995 IEEE
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-3180-X
DOI :
10.1109/NSSMIC.1995.510496
