Wavelet-based Rician noise removal for magnetic resonance imaging

被引：410
|
作者：
Nowak, RD [1 ]
机构：
[1] Rice Univ, Dept Elect & Comp Engn, Houston, TX 77251 USA
来源：
IEEE TRANSACTIONS ON IMAGE PROCESSING | 1999年 / 8卷 / 10期
基金：
美国国家科学基金会;
关键词：
denoising; filtering; magnetic resonance imaging; wavelets;
D O I：
10.1109/83.791966
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：1408 / 1419
页数：12
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