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Conference Papers Year : 2008

Impact of Rician Adapted Non-Local Means Filtering on HARDI

Maxime Descoteaux
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Rachid Deriche
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In this paper we study the impact of denoising the raw high angular resolution diffusion imaging (HARDI) data with the Non-Local Means filter adapted to Rician noise (NLMr). We first show that NLMr filtering improves robustness of apparent diffusion coefficient (ADC) and orientation distribution function (ODF) reconstructions from synthetic HARDI datasets. Our results suggest that the NLMr filtering improve the quality of anisotropy maps computed from ADC and ODF and improve the coherence of q-ball ODFs with the underlying anatomy while not de- grading angular resolution. These results are shown on a biological phan- tom with known ground truth and on a real human brain dataset. Most importantly, we show that multiple measurements of diffusion-weighted (DW) images and averaging these images along each direction can be avoided because NLMr filtering of the individual DW images produces better quality generalized fractional anisotropy maps and more accurate ODF fields than when computed from the averaged DW datasets.


Medical Imaging
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Dates and versions

inria-00423318 , version 1 (09-10-2009)



Maxime Descoteaux, Nicolas Wiest-Daesslé, Sylvain Prima, Christian Barillot, Rachid Deriche. Impact of Rician Adapted Non-Local Means Filtering on HARDI. Medical image computing and computer-assisted intervention - MICCAI 2008, Sep 2008, New-York, United States. ⟨10.1007/978-3-540-85990-1_15⟩. ⟨inria-00423318⟩
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