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Abstract #3370

Shall we use denoising in the preprocessing of diffusion weighted imaging?

Maryam Afzali1, Hu Cheng1, and Sharlene Newman1

1Department of psychological and brain sciences, Indiana University, Bloomington, IN, United States

Many denoising techniques have been proposed in an attempt to remedy the low signal-to-noise ratio (SNR) of diffusion weighted images (DWI) [1-3], especially with high b values. It was shown that denoising might benefit DWI data processing such as fiber tracking [4]. However, denoising is not widely accepted as a mandatory step in the preprocessing of DWI data due to little well documented study about the effect of denoising. In this work, we tested if denoising can overcome the low SNR in tensor based diffusion analysis and fiber tracking.

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