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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http://www.hal.inserm.fr/inserm-00601866
Contributeur : Pierrick Coupé <>
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Dernière modification le : mardi 10 octobre 2017 - 11:22:02
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José 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/j.media.2011.04.003〉. 〈inserm-00601866〉

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