Papers Diffusion MRI
“Diffusion MRI” 태그가 달린 논문 213편 · 필터 해제
Inverting brain grey matter models with likelihood-free inference: a tool for trustable cytoarchitecture measurements
Effective characterisation of the brain grey matter cytoarchitecture with quantitative sensitivity to soma density and volume remains an unsolved challenge in diffusion MRI (dMRI). Solving the problem of relating the dMR…
Diffusion MRISelf-Learned Kernel Low Rank Approach TO Accelerated High Resolution 3D Diffusion MRI
Diffusion Magnetic Resonance Imaging (dMRI) is a promising method to analyze the subtle changes in the tissue structure. However, the lengthy acquisition time is a major limitation in the clinical application of dMRI. Di…
compressed sensingDiffusion MRIEffectiveness of regional diffusion MRI measures in distinguishing multiple sclerosis abnormalities within the cervical spinal cord
Multiple sclerosis is an inflammatory disorder of the central nervous system. Quantitative MRI has huge potential to provide intrinsic and normative values of tissue properties useful for diagnosis, prognosis and ultimat…
Diffusion MRIPrognosisQuantitative MRIEvaluation of distortion correction methods in diffusion MRI of the spinal cord
Background: Magnetic field inhomogeneities generate important geometric distortions in reconstructed echo-planar images. Various procedures were proposed for correcting these distortions on brain images; yet, few neuroim…
Diffusion MRIdistortion correctionReproducibility and Evolution of Diffusion MRI Measurements within the Cervical Spinal Cord in Multiple Sclerosis
In Multiple Sclerosis (MS), there is a large discrepancy between the clinical observations and how the pathology is exhibited on brain images, this is known as the clinical-radiological paradox (CRP). One of the hypothes…
Diffusion MRIA computational geometry approach for modeling neuronal fiber pathways
We propose a novel and efficient algorithm to model high-level topological structures of neuronal fibers. Tractography constructs complex neuronal fibers in three dimensions that exhibit the geometry of white matter path…
Diffusion MRIClinica: an open source software platform for reproducible clinical neuroscience studies
We present Clinica (www.clinica.run), an open-source software platform designed to make clinical neuroscience studies easier and more reproducible. Clinica aims for researchers to i) spend less time on data management an…
BIG-bench Machine LearningDiffusion MRIManagementPhilosophyQ-space Conditioned Translation Networks for Directional Synthesis of Diffusion Weighted Images from Multi-modal Structural MRI
Current deep learning approaches for diffusion MRI modeling circumvent the need for densely-sampled diffusion-weighted images (DWIs) by directly predicting microstructural indices from sparsely-sampled DWIs. However, the…
Diffusion MRITranslationIs Perfect Filtering Enough Leading to Perfect Phase Correction for dMRI data?
Being complex-valued and low in signal-to-noise ratios, magnitude-based diffusion MRI is confounded by the noise-floor that falsely elevates signal magnitude and incurs bias to the commonly used diffusion indices, such a…
Diffusion MRIVolterraNet: A higher order convolutional network with group equivariance for homogeneous manifolds
Convolutional neural networks have been highly successful in image-based learning tasks due to their translation equivariance property. Recent work has generalized the traditional convolutional layer of a convolutional n…
Diffusion MRITranslationQuantitative mapping of the brain's structural connectivity using diffusion MRI tractography: a review
Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo mapping of the brain's white matter connections at macro scale. Over the last two decades, the study of brain…
Diffusion MRIMulti-compartment diffusion MRI, T2 relaxometry and myelin water imaging as neuroimaging descriptors for anomalous tissue detection
Multiple sclerosis (MS) is an inflammatory and neurodegenerative disease characterized by diffuse and focal areas of tissue loss. Conventional MRI techniques such as T1-weighted and T2-weighted scans are generally used i…
Diffusion MRIPrognosisSpecificityBrainNetGAN: Data augmentation of brain connectivity using generative adversarial network for dementia classification
Alzheimer's disease (AD) is the most common age-related dementia. It remains a challenge to identify the individuals at risk of dementia for precise management. Brain MRI offers a noninvasive biomarker to detect brain ag…
Binary ClassificationClassificationData AugmentationDiffusion MRI+33D-QCNet -- A Pipeline for Automated Artifact Detection in Diffusion MRI images
Artifacts are a common occurrence in Diffusion MRI (dMRI) scans. Identifying and removing them is essential to ensure the accuracy and viability of any post processing carried out on these scans. This makes QC (quality c…
Artifact DetectionDiffusion MRIEquivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data
We present a rotation-equivariant unsupervised learning framework for the sparse deconvolution of non-negative scalar fields defined on the unit sphere. Spherical signals with multiple peaks naturally arise in Diffusion …
Diffusion MRIMulti-Texture GAN: Exploring the Multi-Scale Texture Translation for Brain MR Images
Inter-scanner and inter-protocol discrepancy in MRI datasets are known to lead to significant quantification variability. Hence image-to-image or scanner-to-scanner translation is a crucial frontier in the area of medica…
AnatomyDiffusion MRIMedical Image AnalysisSuper-Resolution+1Rotation-Equivariant Deep Learning for Diffusion MRI
Convolutional networks are successful, but they have recently been outperformed by new neural networks that are equivariant under rotations and translations. These new networks work better because they do not struggle wi…
Deep LearningDiffusion MRILesion SegmentationSingle-Shell NODDI Using Dictionary Learner Estimated Isotropic Volume Fraction
Neurite orientation dispersion and density imaging (NODDI) enables the assessment of intracellular, extracellular and free water signals from multi-shell diffusion MRI data. It is an insightful approach to characterize b…
Dictionary LearningDiffusion MRILongitudinal diffusion MRI analysis using Segis-Net: a single-step deep-learning framework for simultaneous segmentation and registration
This work presents a single-step deep-learning framework for longitudinal image analysis, coined Segis-Net. To optimally exploit information available in longitudinal data, this method concurrently learns a multi-class s…
Diffusion MRISegmentationPatch2Self: Denoising Diffusion MRI with Self-Supervised Learning
Diffusion-weighted magnetic resonance imaging (DWI) is the only non-invasive method for quantifying microstructure and reconstructing white-matter pathways in the living human brain. Fluctuations from multiple sources cr…
DenoisingDiffusion MRISelf-Supervised Learning