I Diaz, P Boulanger, R Greiner and A Murtha (2011). A Critical Review of the Effect of De-noising Algorithms on MRI Brain. In 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'11), 4 pages, Boston, USA. September 2011. IEEE.
One can find in the literature numerous techniques to reduce noise in Magnetic Resonance Images (MRI). This paper critically reviews modern de-noising algorithms (Gaussian filter, anisotropic diffusion, wavelet, and non-local mean) in terms of their efficiency, statistical assumptions, and their ability to improve brain tumor segmentation results. We will show that although the different techniques do reduce the noise, many generate artifacts that are incompatible with precise brain tumor segmentation. We also show that the non-local means algorithm is the best de-noising technique for brain tumor segmentation.
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