ArticleNeuroImage2023
Denoising of diffusion MRI in the cervical spinal cord - effects of denoising strategy and acquisition on intra-cord contrast, signal modeling, and feature conspicuity.
Article in NeuroImage, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
18 citing papers in PubMed.
- Standard Model Imaging in the Brain and Spinal Cord of MS Patients: Initial Assessment and Comparison to Diffusion Tensor Imaging.NMR in biomedicine · 2026Article
- ISME-incoherent sampling of multi-echo data to minimize cardiac-induced noise in brain maps ofMagnetic resonance in medicine · 2026Article
- CoSpine open access simultaneous cortico-spinal fMRI database of thermal pain and motor tasks.Scientific data · 2025Article
- Comparing single-shot EPI and 2D-navigated, multi-shot EPI diffusion tensor imaging acquisitions in the lumbar spinal cord at 3T.Magnetic resonance imaging · 2025Article
- Evaluating the impact of denoising diffusion MRI data on tractometry metrics of optic tract abnormalities in glaucoma.Scientific reports · 2025Article
- In Vivo Characterization of Magnetic Inclusions in the Subcortex From Nonexponential Transverse Relaxation Decay.NMR in biomedicine · 2025Article
- Aquaporin-4 inhibition alters cerebral glucose dynamics predominantly in obese animals: an MRI study.Scientific reports · 2025Article
- Characterization of neurite and soma organization in the brain and spinal cord with diffusion MRI.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Closing the diagnostic gap: A narrative review of recent advances in functional MRI diagnostics in spinal cord injury.Brain & spine · 2025Review
- Reproducible Spinal Cord Quantitative MRI Analysis with the Spinal Cord Toolbox.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2024Review
- In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI.Human brain mapping · 2024Article
- Diffusion MRI head motion correction methods are highly accurate but impacted by denoising and sampling scheme.Human brain mapping · 2024Article
- Denoising diffusion MRI: Considerations and implications for analysis.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Multi-view fusion of diffusion MRI microstructural models: a preterm birth study.Frontiers in neuroscience · 2024Article
- Diffusion MRI with Machine Learning.Imaging neuroscience (Cambridge, Mass.) · 2024Article
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- Advanced spinal cord MRI in multiple sclerosis: Current techniques and future directions.NeuroImage. Clinical · 2022Review
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Quantitative diffusion MRI (dMRI) is a promising technique for evaluating the spinal cord in health and disease. However, low signal-to-noise ratio (SNR) can impede interpretation and quantification of these images. The purpose of this study is to evaluate several dMRI denoising approaches on their ability to improve the quality, reliability, and accuracy of quantitative diffusion MRI of the spinal cord. We evaluate three denoising approaches (Non-Local Means, Marchenko-Pastur PCA, and a newly proposed Patch2Self algorithm) and conduct five experiments to validate the denoising performance on clinical-quality and commonly-acquired dMRI acquisitions: 1) a phantom experiment to assess denoising error and bias; 2) a multi-vendor, multi-acquisition open experiment for both qualitative and quantitative evaluation of noise residuals; 3) a bootstrapping experiment to estimate uncertainty of parametric maps; 4) an assessment of spinal cord lesion conspicuity in a multiple sclerosis group; and 5) an evaluation of denoising for advanced parametric multi-compartment modeling. We find that all methods improve signal-to-noise ratio and conspicuity of MS lesions in individual diffusion weighted images (DWIs), but MPPCA and Patch2Self excel at improving the quality and intra-cord contrast of diffusion weighted images - removing signal fluctuations due to thermal noise while improving precision of estimation of diffusion parameters even with very few DWIs (i.e., 16-32) typical of clinical acquisitions. These denoising approaches hold promise for facilitating reliable diffusion observations and measurements in the spinal cord to investigate biological and pathological processes.
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