WAVELET SHRINKAGE PRE-FILTERING OF MR IMAGES FOR BRAIN TISSUE SEGMENTATION

摘要

Brain tissue image data is pre-processed to remove the skull therefrom. An estimation is made of the noise level in the signal to determine if it is severely noisy. For those parts of the data that are not severely noisy, the tissue is segmented using FCM clustering. For those parts of the data that are severely noisy, the tissue is wavelet pre-filtered before the tissue image contained therein is segmented. The wavelet pre-filtering involves estimating a shrinkage parameter, wavelet transforming the data, coefficient shrinkage of the transformed data and inverse wavelet transforming of the reduced set of coefficients.