Wavelet-based Rician noise removal for magnetic resonance imaging

Author

Nowak, Robert D.

Author_Institution

Dept. of Electr. & Comput. Eng., Rice Univ., Houston, TX, USA

Volume

8

Issue

10

fYear

1999

fDate

10/1/1999 12:00:00 AM

Firstpage

1408

Lastpage

1419

Abstract

It is well known that magnetic resonance magnitude image data obey a Rician distribution. Unlike additive Gaussian noise, Rician “noise” is signal-dependent, 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-dependent bias to the data that reduces image contrast. This paper studies wavelet-domain filtering methods for Rician noise removal. We present a novel wavelet-domain filter that adapts to variations in both the signal and the noise

Keywords

biomedical MRI; filtering theory; image processing; medical image processing; noise; statistical analysis; wavelet transforms; Rician distribution; SNR; image contrast; low signal-to-noise ratio; magnetic resonance imaging; magnetic resonance magnitude image data; random fluctuations; signal-dependent bias; signal-dependent noise; wavelet-based Rician noise removal; wavelet-domain filter; wavelet-domain filtering methods; Additive noise; Filtering; Fluctuations; Gaussian noise; Magnetic noise; Magnetic resonance; Magnetic resonance imaging; Noise reduction; Rician channels; Signal to noise ratio;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.791966

Filename

791966