Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning
S Fadnavis, J Batson… - Advances in Neural …, 2020 - proceedings.neurips.cc
Diffusion-weighted magnetic resonance imaging (DWI) is the only non-invasive method for
quantifying microstructure and reconstructing white-matter pathways in the living human …
quantifying microstructure and reconstructing white-matter pathways in the living human …
Non Local Spatial and Angular Matching: Enabling higher spatial resolution diffusion MRI datasets through adaptive denoising
Diffusion magnetic resonance imaging (MRI) datasets suffer from low Signal-to-Noise Ratio
(SNR), especially at high b-values. Acquiring data at high b-values contains relevant …
(SNR), especially at high b-values. Acquiring data at high b-values contains relevant …
DDM: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models
Magnetic resonance imaging (MRI) is a common and life-saving medical imaging technique.
However, acquiring high signal-to-noise ratio MRI scans requires long scan times, resulting …
However, acquiring high signal-to-noise ratio MRI scans requires long scan times, resulting …
[HTML][HTML] NOise reduction with DIstribution Corrected (NORDIC) PCA in dMRI with complex-valued parameter-free locally low-rank processing
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 …
range of neuroscientific and clinical applications. However, high-resolution dMRI, which is …
Denoising of diffusion MRI using random matrix theory
We introduce and evaluate a post-processing technique for fast denoising of diffusion-
weighted MR images. By exploiting the intrinsic redundancy in diffusion MRI using universal …
weighted MR images. By exploiting the intrinsic redundancy in diffusion MRI using universal …
[HTML][HTML] SDnDTI: Self-supervised deep learning-based denoising for diffusion tensor MRI
Diffusion tensor magnetic resonance imaging (DTI) is a widely adopted neuroimaging
method for the in vivo mapping of brain tissue microstructure and white matter tracts …
method for the in vivo mapping of brain tissue microstructure and white matter tracts …
QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data
Diffusion-weighted magnetic resonance imaging (dMRI) is the primary method for
noninvasively studying the organization of white matter in the human brain. Here we …
noninvasively studying the organization of white matter in the human brain. Here we …
Q-space deep learning: twelve-fold shorter and model-free diffusion MRI scans
Numerous scientific fields rely on elaborate but partly suboptimal data processing pipelines.
An example is diffusion magnetic resonance imaging (diffusion MRI), a non-invasive …
An example is diffusion magnetic resonance imaging (diffusion MRI), a non-invasive …
[HTML][HTML] Realistic simulation of artefacts in diffusion MRI for validating post-processing correction techniques
In this paper we demonstrate a simulation framework that enables the direct and quantitative
comparison of post-processing methods for diffusion weighted magnetic resonance (DW …
comparison of post-processing methods for diffusion weighted magnetic resonance (DW …
Sparse Reconstruction Challenge for diffusion MRI: Validation on a physical phantom to determine which acquisition scheme and analysis method to use?
Diffusion magnetic resonance imaging (dMRI) is the modality of choice for investigating in-
vivo white matter connectivity and neural tissue architecture of the brain. The diffusion …
vivo white matter connectivity and neural tissue architecture of the brain. The diffusion …