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Denoising diffusion MRI: Considerations and implications for analysis

  • 0Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom.
Imaging Neuroscience (cambridge, Mass.) +

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August 13, 2025

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August 13, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

This study introduces new criteria to evaluate diffusion MRI denoising methods, finding that complex-domain denoising offers superior performance over magnitude-domain approaches for improved accuracy and resolution.

Area Of Science

  • Medical Imaging
  • Neuroimaging
  • Signal Processing

Background

  • Noise in diffusion MRI (dMRI) reduces measurement accuracy and precision.
  • Existing characterizations of dMRI denoising methods have gaps in assessing bias and efficacy.
  • Noise floor effects and uncertainty increase are critical concerns in dMRI analysis.

Purpose Of The Study

  • To establish objective criteria for evaluating dMRI denoising performance.
  • To assess the efficacy of various denoising approaches, including bias reduction and spatial resolution preservation.
  • To compare complex-domain versus magnitude-domain denoising in dMRI.

Main Methods

  • Development of a comprehensive evaluation framework for dMRI denoising.
  • Acquisition of complex dMRI datasets with multiple repeats across different signal-to-noise ratio (SNR) regimes.
  • Application and comparison of exemplar denoising algorithms (Non-Local Means, MPPCA, NORDIC) against a gold standard.

Main Results

  • All tested denoising methods reduced noise variance but not always noise floor biases.
  • Spatial resolution was penalized by all methods, with variations based on implementation.
  • Complex-domain denoising demonstrated advantages over magnitude-domain denoising across all evaluated criteria.

Conclusions

  • Objective criteria are essential for robust dMRI denoising evaluation.
  • Complex-domain dMRI denoising is superior for improving signal quality, reducing bias, and preserving spatial resolution.
  • Further research is needed to refine gold standards for dMRI denoising validation.

Keywords:

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