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NOise reduction with DIstribution Corrected (NORDIC) PCA in dMRI with complex-valued parameter-free locally low-rank processing
- Source :
- NeuroImage, Vol 226, Iss, Pp 117539-(2021), NeuroImage
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- Diffusion-weighted magnetic resonance imaging (dMRI) has found great utility for a wide range of neuroscientific and clinical applications. However, high-resolution dMRI, which is required for improved delineation of fine brain structures and connectomics, is hampered by its low signal-to-noise ratio (SNR). Since dMRI relies on the acquisition of multiple different diffusion weighted images of the same anatomy, it is well-suited for denoising methods that utilize correlations across the image series to improve the apparent SNR and the subsequent data analysis. In this work, we introduce and quantitatively evaluate a comprehensive framework, NOise Reduction with Distribution Corrected (NORDIC) PCA method for processing dMRI. NORDIC uses low-rank modeling of g-factor-corrected complex dMRI reconstruction and non-asymptotic random matrix distributions to remove signal components which cannot be distinguished from thermal noise. The utility of the proposed framework for denoising dMRI is demonstrated on both simulations and experimental data obtained at 3 Tesla with different resolutions using human connectome project style acquisitions. The proposed framework leads to substantially enhanced quantitative performance for estimating diffusion tractography related measures and for resolving crossing fibers as compared to a conventional/state-of-the-art dMRI denoising method.HighlightsWe propose a framework, NORDIC, for denoising complex valued dMRI data using Gaussian statisticsThe effectiveness of the proposed denoising method is distinguished by the ability to remove only signal which cannot be distinguished from thermal noiseThe proposed method outperforms a state-of-art method for denoising dMRI in terms of fiber orientation dispersionQuantitative evaluation of NORDIC across different resolutions and SNR using human connectome type acquisitions and analysis shows up to 6 fold improvement in apparent SNR for 0.9mm whole brain dMRI at 3T.
- Subjects :
- Image Series
Connectomics
Rank (linear algebra)
Computer science
Cognitive Neuroscience
Noise reduction
Brain imaging
Signal-To-Noise Ratio
Article
050105 experimental psychology
Diffusion MRI
lcsh:RC321-571
03 medical and health sciences
0302 clinical medicine
Neuroimaging
Singular value decomposition
Connectome
Image Processing, Computer-Assisted
Range (statistics)
medicine
Humans
0501 psychology and cognitive sciences
Diffusion Tractography
lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry
Multiband
Denoising
Human Connectome Project
Human connectome project
medicine.diagnostic_test
business.industry
05 social sciences
Brain
Magnetic resonance imaging
Pattern recognition
Simultaneous multi-slice
Diffusion Magnetic Resonance Imaging
Neurology
Computer Science::Computer Vision and Pattern Recognition
Artificial intelligence
Artifacts
business
Random matrix
Algorithms
030217 neurology & neurosurgery
Subjects
Details
- ISSN :
- 10538119
- Volume :
- 226
- Database :
- OpenAIRE
- Journal :
- NeuroImage
- Accession number :
- edsair.doi.dedup.....cafa6324c95edaa02afc302a622c684e
- Full Text :
- https://doi.org/10.1016/j.neuroimage.2020.117539