Does a sharper image lead to better results? Diffusion MRI denoising put to the test
2025.08.05
Research
Researchers from the National Institute of Physiological Sciences evaluated the impact of noise removal algorithms on dMRI data for detecting tissue abnormalities in glaucoma.
Summary
Researchers from the National Institute of Physiological Sciences found that ‘denoising’, a method used to clean diffusion-weighted MRI (dMRI) data, alters the appearance of dMRI images and the estimated signal-to-noise ratio of the data, but had limited impacts on the ability to detect optic tract abnormalities in glaucoma.Result
For decades, MRI (magnetic resonance imaging) has been a powerful way to see inside the human brain. A specialized form, diffusion-weighted MRI (dMRI), can measure tissue properties of fiber pathways in the brain by measuring the movement of water molecules. Since dMRI is applicable to living humans, it becomes a valuable tool for studying the neurological changes of fiber pathways caused by disorders.
However, dMRI data often suffers from the presence of ‘noise’, limiting its ability to identify biological signals related to health and disease. To date, several ‘denoising’ algorithms have been proposed to remove noise from dMRI data. Now, in a study to be published in Scientific Reports, researchers from the National Institute of Physiological Sciences have sought to determine in what aspect ‘denoising’ can help identify disease-related changes in fiber pathways.
“We decided to check for ourselves if the available denoising techniques were truly beneficial for empirical data,” explains Daiki Taguma, lead author of the study.
The research team tested two common denoising techniques on real-world data: brain scans from healthy individuals and patients with glaucoma. Previous research had already shown that dMRI could detect tissue abnormalities in the fiber pathway named the optic tract in glaucoma, making it an ideal test case.
They found that denoising altered the appearance of dMRI images and increased the estimated signal-to-noise ratio, a key metric for evaluating image quality. However, they also found that when they analyzed dMRI data of the optic tract, denoising had a limited impact on the differences between healthy controls and patients with glaucoma.
These results suggest that at present, denoising may improve dMRI data in some aspect, but does not significantly alter results concerning disease-related changes in fiber pathways. The study concluded that the benefits of current denoising methods depend on the context and purpose of the analysis.
These findings mark an important step toward refining how dMRI is used in both clinical and research settings. By understanding what works, researchers can better harness dMRI’s potential, advancing our ability to detect and understand the impact of diseases on fiber pathways in the brain.
Left: Study design.We analyzed dMRI data acquired from 17 patients with glaucoma and 30 healthy controls, and then compared the data with and without denoising.
Right: Comparison between data with and without denoising.While denoising altered the image appearance (top panels), it did not significantly impact the results of the analysis identifying tissue differences in the fiber pathway (optic tract) between patients with glaucoma and controls (bottom panel).
Right: Comparison between data with and without denoising.While denoising altered the image appearance (top panels), it did not significantly impact the results of the analysis identifying tissue differences in the fiber pathway (optic tract) between patients with glaucoma and controls (bottom panel).
Researchers
Hiromasa Takemura (National Institute for Physiological Sciences, SOKENDAI,Core for Spin Life Sciences, Okazaki Collaborative Platform )Daiki Taguma (National Institute for Physiological Sciences, SOKENDAI)
Shumpei Ogawa (Jikei University School of Medicine)
Journal
Title: Evaluating the impact of denoising diffusion MRI data on tractometry metrics of optic tract abnormalities in glaucomaAuthors: Daiki Taguma, Shumpei Ogawa, Hiromasa Takemura
Journal: Scientific Reports
Issue: 15
Date: 2025/07/16
URL (abstract): https://www.nature.com/articles/s41598-025-10947-6
DOI: https://doi.org/10.1038/s41598-025-10947-6
Grant
the Grants-in-Aid for Japan Society for the Promotion of Science (KAKENHI)
the Joint Research Program of the National Institute for Physiological Sciences
the MEXT Promotion of Development of a Joint Usage/Research System Project: Coalition of Universities of Research Excellence Program (CURE).
the Joint Research Program of the National Institute for Physiological Sciences
the MEXT Promotion of Development of a Joint Usage/Research System Project: Coalition of Universities of Research Excellence Program (CURE).