https://onlinelibrary.wiley.com/doi/full/10.1002/hbm.70142
We’re excited to share our latest breakthrough in diffusion MRI research! In our new paper, “Denoising Improves Cross‐Scanner and Cross‐Protocol Test–Retest Reproducibility of Diffusion Tensor and Kurtosis Imaging,” we demonstrate how state‐of‐the‐art MPPCA denoising techniques can dramatically reduce variability across different scanners and protocols.
Our study shows that denoising can lower test–retest variability from 15%–20% down to just 5%–10%. Denoising methods reduced the noise floor by up to 60%, which not only improved the precision of diffusion tensor (DTI) and kurtosis imaging (DKI) metrics but also resulted in a significant reduction in the required sample sizes—by as much as 40%–70%—for detecting a 5% effect size between sample populations.
Our research demonstrates that by sharpening image quality and reducing outliers (in some cases by over 70%), our denoising approach paves the way for more efficient and cost-effective investigations into brain microstructure.
Discover how this innovative approach can transform MRI data analysis, improve diagnostic accuracy, and drive forward the clinical translation of advanced imaging techniques. Learn more about the study and explore our suite of cutting-edge MRI processing tools at micsi. Stay tuned for more updates as we continue to push the boundaries of medical imaging technology!
Ades-Aron et al. Denoising Improves Cross-Scanner and Cross-Protocol Test-Retest Reproducibility of Diffusion Tensor and Kurtosis Imaging. Comparisons: Prisma scanner (scan-rescan TE=92ms), Skyra scanner (scan-rescan TE=127me), Prisma (TE=92ms vs TE=127ms), Prisma (TE=127ms) vs Skyra (TE=127ms).