Wavelet-based Rician noise removal for magnetic resonance imaging

It is well known that magnetic resonance magnitude image data obey a Rician distribution. Unlike additive Gaussian noise, Rician "noise" is signal-dep endent, and separating signal from noise is a difficult task. Rician noise is especially problematic in low signal-to noise ratio (SNR) regimes where it not only causes random fluctuations, but also introduces a signal-depend ent bias to the data that reduces image contrast. This paper studies wavele t-domain filtering methods for Rician noise removal. We present a novel wav elet-domain filter that adapts to variations in both the signal and the noi se.