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New methods for MRI denoising based on sparseness and self-similarity.

Abstract : This paper proposes two new methods for the three-dimensional denoising of magnetic resonance images that exploit the sparseness and self-similarity properties of the images. The proposed methods are based on a three-dimensional moving-window discrete cosine transform hard thresholding and a three-dimensional rotationally invariant version of the well-known nonlocal means filter. The proposed approaches were compared with related state-of-the-art methods and produced very competitive results. Both methods run in less than a minute, making them usable in most clinical and research settings.
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Submitted on : Monday, June 20, 2011 - 11:46:34 PM
Last modification on : Saturday, June 25, 2022 - 8:50:39 PM
Long-term archiving on: : Wednesday, September 21, 2011 - 2:26:56 AM


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José V. Manjón, Pierrick Coupé, Antonio Buades, D. Louis Collins, Montserrat Robles. New methods for MRI denoising based on sparseness and self-similarity.. Medical Image Analysis, Elsevier, 2012, 16 (1), pp.18-27. ⟨10.1016/⟩. ⟨inserm-00601866⟩



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