Adaptive anisotropic noise filtering for magnitude MR data

Jan Sijbers; Arnold Jan den Dekker; Marleen Verhoye; Anne-Marie Van der Linden; Dirk Van Dyck

doi:10.1117/12.348541

21 May 1999 Adaptive anisotropic noise filtering for magnitude MR data

Jan Sijbers, Arnold Jan den Dekker, Marleen Verhoye, Anne-Marie Van der Linden, Dirk Van Dyck

Proceedings Volume 3661, Medical Imaging 1999: Image Processing; (1999) https://doi.org/10.1117/12.348541
Event: Medical Imaging '99, 1999, San Diego, CA, United States

Abstract

In general, conventional noise filtering schemes applied to magnitude magnetic resonance (MR) images are based on Gauss distributed noise. Magnitude MR data, however, are Rice distributed. Not incorporating this knowledge leads inevitably to biased results, in particular when applying those filters in regions with low signal-to-noise ratio. In this work, we show how the Rice data probability distribution can be incorporated to construct a noise filter that is far less biased.

Citation Download Citation

Jan Sijbers, Arnold Jan den Dekker, Marleen Verhoye, Anne-Marie Van der Linden, and Dirk Van Dyck "Adaptive anisotropic noise filtering for magnitude MR data", Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); https://doi.org/10.1117/12.348541

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