Tracking Algorithm For De-Noishing of MR Brain Images
J. Jaya, K. Thanushkodi, Marcus Karnan · 2009
Summary In this paper, we demonstrate Implementations of denoising algorithms on MR brain images. A major concern in de-noising MR brain images is the poor quality images secondary to a worsening signal-to-noise ratio (SNR). This paper gives some useful insight on the application of preprocessing techniques towards segmenting and labeling the brain images. Promising results are reported. The Proposed technique consists of four processing stages. In the first stage, the MRI brain image is acquired from MRI brain data set to MATLAB 7.1. After acquisition the MRI is given to the pre-processing stage, here the film artifacts (labels) are removed. In the third stage, the high frequency components and noise are removed from MRI using the following ways.1. Median filter 2.Weighted median 3.Adaptive filter. Finally the performance of above filters are measured and evaluated.