Postprocessing of MR images: noise filtering and distortion correction

Juan M. Parra Robles; Evelio R Gonzalez M.D.; Juan E. Paz; Nancy A. Alvarez Roca

doi:10.1117/12.310861

24 June 1998 Postprocessing of MR images: noise filtering and distortion correction

Juan M. Parra Robles, Evelio R Gonzalez M.D., Juan E. Paz, Nancy A. Alvarez Roca

Proceedings Volume 3338, Medical Imaging 1998: Image Processing; (1998) https://doi.org/10.1117/12.310861
Event: Medical Imaging '98, 1998, San Diego, CA, United States

Abstract

The quality of Magnetic Resonance (MR) images depends on several factors: static and radiofrequency field nonuniformities, gradient field nonlinearities, random noise, etc. Distortion correction and noise filtering not only increase the image visual quality but are indispensable steps prior to further applications, such as: image segmentation, quantitative analysis, 3D visualization, surgical planning, stereotactic neurosurgery. Imaging experiments were performed on a 0.1T MR scanner (Giroimag 02), developed in our center, using a head coil. Intensity and geometric distortions were corrected using correction maps obtained from images of suitable phantoms. The applied post-processing methods improved the image quality. Uniformity was increased significantly (about 20%) with the obtained correction matrix. Geometric correction reduced the distortion to sub-millimeter values. Significant improvements in S/N ratio were obtained by means of the noise filtering procedures tested. The edge information was preserved acceptably. Adaptive nonlinear filters (modified Gaussian filter) and Wavelet Denoising provided the best results increasing the image S/N ratio in more than 90% with relative minor resolution loss. All these techniques were implemented and tested upon a wide range of images and form a set of tools incorporated to the Image Acquisition System for Cuban MR scanners Giroimag.

Citation Download Citation

Juan M. Parra Robles, Evelio R Gonzalez M.D., Juan E. Paz, and Nancy A. Alvarez Roca "Postprocessing of MR images: noise filtering and distortion correction", Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); https://doi.org/10.1117/12.310861

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