Denoising for Magnetic Resonance Imaging
نویسنده
چکیده
The utility of magnetic resonance imaging can often be diminished in regions and tissues that suffer from a low signal to noise ratio (SNR). This is especially the case in quantitative MRI where the quantitative parameters being measured can be easily biased by low SNR. In this study, the utility of different denoising algorithms, namely non-local means, bilateral filtering, and block-match and 3D filtering (BM3D) were evaluated. BM3D offered the best denoising results while maintaining visual signal quality. This algorithm was further enhanced by making it locally adaptive to the region of interest being measured. It was also shown that genetic algorithms could be easily used to find robust solutions to the multi-dimensional parameter space that the inputs of BM3D encompasses.
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