Preconditioning methods for improved convergence rates in iterative reconstructions

摘要: Because of the characteristics tomographic inversion problem, iterative reconstruction techniques often suffer from poor convergence rates-especially at high spatial frequencies. By using preconditioning methods, properties most methods can be greatly enhanced without changing their ultimate solution. To increase speed, spatially invariant filters that designed system response and implemented 2-D frequency-domain filtering have been applied. In a sample application, reconstructions noiseless, simulated projection data, were performed preconditioned conventional steepest-descent algorithms. The demonstrated residuals up to factor 30 lower than assisted algorithms same iteration. Applications these regularized data containing Poisson noise showed similar, although not as dramatic, behavior. >