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Journal Articles Medical Image Analysis Year : 2012

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

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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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Dates and versions

inserm-00601866 , version 1 (20-06-2011)

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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, 2012, 16 (1), pp.18-27. ⟨10.1016/j.media.2011.04.003⟩. ⟨inserm-00601866⟩
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