Comparison of statistical methods in MR imaging
- 1 March 1991
- journal article
- research article
- Published by Wiley in International Journal of Imaging Systems and Technology
- Vol. 3 (1) , 33-39
- https://doi.org/10.1002/ima.1850030106
Abstract
The problem of recovering the true underlying scene from a noisy image is considered. Several methods are compared empirically by applying them to magnetic resonance (MR) images. It turns out that a simple method, the Gaussian window filter, gives good results. This method requires only “instantaneous” processing.Keywords
This publication has 9 references indexed in Scilit:
- Noise reduction using markov random fieldsJournal of Magnetic Resonance (1969), 1991
- Why MEM does not work in MR image reconstructionMagnetic Resonance in Medicine, 1990
- On the Statistical Analysis of Dirty PicturesJournal of the Royal Statistical Society Series B: Statistical Methodology, 1986
- Statistics, images, and pattern recognitionThe Canadian Journal of Statistics / La Revue Canadienne de Statistique, 1986
- Truncation Artifacts in Magnetic Resonance ImagingMagnetic Resonance in Medicine, 1985
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of ImagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1984
- Digital image smoothing and the sigma filterComputer Vision, Graphics, and Image Processing, 1983
- Image restoration by a powerful maximum entropy methodComputer Vision, Graphics, and Image Processing, 1983
- Robust StatisticsPublished by Wiley ,1981