Papers Diffusion MRI
“Diffusion MRI” 태그가 달린 논문 213편 · 필터 해제
Scattering approach to diffusion quantifies axonal damage in brain injury
Early diagnosis and noninvasive monitoring of neurological disorders require sensitivity to elusive cellular-level alterations that occur much earlier than volumetric changes observable with the millimeter-resolution of …
Diffusion MRISensitivityThree-Dimensional Diffusion-Weighted Multi-Slab MRI With Slice Profile Compensation Using Deep Energy Model
Three-dimensional (3D) multi-slab acquisition is a technique frequently employed in high-resolution diffusion-weighted MRI in order to achieve the best signal-to-noise ratio (SNR) efficiency. However, this technique is l…
Diffusion MRISpatial-Angular Representation Learning for High-Fidelity Continuous Super-Resolution in Diffusion MRI
Diffusion magnetic resonance imaging (dMRI) often suffers from low spatial and angular resolution due to inherent limitations in imaging hardware and system noise, adversely affecting the accurate estimation of microstru…
Diffusion MRIparameter estimationRepresentation LearningSuper-ResolutionSelf-Supervised Diffusion MRI Denoising via Iterative and Stable Refinement
Magnetic Resonance Imaging (MRI), including diffusion MRI (dMRI), serves as a ``microscope'' for anatomical structures and routinely mitigates the influence of low signal-to-noise ratio scans by compromising temporal or …
DenoisingDiffusion MRIPolyhedra Encoding Transformers: Enhancing Diffusion MRI Analysis Beyond Voxel and Volumetric Embedding
Diffusion-weighted Magnetic Resonance Imaging (dMRI) is an essential tool in neuroimaging. It is arguably the sole noninvasive technique for examining the microstructural properties and structural connectivity of the bra…
Diffusion MRISFC-GAN: A Generative Adversarial Network for Brain Functional and Structural Connectome Translation
Modern brain imaging technologies have enabled the detailed reconstruction of human brain connectomes, capturing structural connectivity (SC) from diffusion MRI and functional connectivity (FC) from functional MRI. Under…
Diffusion MRIFunctional ConnectivityGenerative Adversarial NetworkTranslationA Steerable Deep Network for Model-Free Diffusion MRI Registration
Nonrigid registration is vital to medical image analysis but remains challenging for diffusion MRI (dMRI) due to its high-dimensional, orientation-dependent nature. While classical methods are accurate, they are computat…
Diffusion MRIMedical Image AnalysisDiff5T: Benchmarking Human Brain Diffusion MRI with an Extensive 5.0 Tesla K-Space and Spatial Dataset
Diffusion magnetic resonance imaging (dMRI) provides critical insights into the microstructural and connectional organization of the human brain. However, the availability of high-field, open-access datasets that include…
BenchmarkingDiffusion MRIImage Reconstruction7 Tesla multimodal MRI dataset of ex-vivo human brain
Ex-vivo MRI offers invaluable insights into the complexity of the human brain, enabling high-resolution anatomical delineation and integration with histopathology, and thus, contributes to both basic and clinical studies…
Diffusion MRIDiversityNew Graphs at the braingraph.org Website for Studying the Aging Brain Circuitry
Human braingraphs or connectomes are widely studied in the last decade to understand the structural and functional properties of our brain. In the last several years our research group has computed and deposited thousand…
Diffusion MRIACE-Net: AutofoCus-Enhanced Convolutional Network for Field Imperfection Estimation with application to high b-value spiral Diffusion MRI
Spatiotemporal magnetic field variations from B0-inhomogeneity and diffusion-encoding-induced eddy-currents can be detrimental to rapid image-encoding schemes such as spiral, EPI and 3D-cones, resulting in undesirable im…
Diffusion MRIImage ReconstructionEquivariant spatio-hemispherical networks for diffusion MRI deconvolution
Each voxel in a diffusion MRI (dMRI) image contains a spherical signal corresponding to the direction and strength of water diffusion in the brain. This paper advances the analysis of such spatio-spherical data by develo…
Diffusion MRIMRI Parameter Mapping via Gaussian Mixture VAE: Breaking the Assumption of Independent Pixels
We introduce and demonstrate a new paradigm for quantitative parameter mapping in MRI. Parameter mapping techniques, such as diffusion MRI and quantitative MRI, have the potential to robustly and repeatably measure biolo…
Diffusion MRIQuantitative MRIMICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI
White matter alterations are increasingly implicated in neurological diseases and their progression. International-scale studies use diffusion-weighted magnetic resonance imaging (DW-MRI) to qualitatively identify change…
Diffusion MRITract-RLFormer: A Tract-Specific RL policy based Decoder-only Transformer Network
Fiber tractography is a cornerstone of neuroimaging, enabling the detailed mapping of the brain's white matter pathways through diffusion MRI. This is crucial for understanding brain connectivity and function, making it …
DecoderDiffusion MRIreinforcement-learningReinforcement LearningA Novel Deep Learning Tractography Fiber Clustering Framework for Functionally Consistent White Matter Parcellation Using Multimodal Diffusion MRI and Functional MRI
Tractography fiber clustering using diffusion MRI (dMRI) is a crucial strategy for white matter (WM) parcellation. Current methods primarily use the geometric information of fibers (i.e., the spatial trajectories) to gro…
ClusteringDiffusion MRITractShapeNet: Efficient Multi-Shape Learning with 3D Tractography Point Clouds
Brain imaging studies have demonstrated that diffusion MRI tractography geometric shape descriptors can inform the study of the brain's white matter pathways and their relationship to brain function. In this work, we inv…
Diffusion MRIBrain age identification from diffusion MRI synergistically predicts neurodegenerative disease
Estimated brain age from magnetic resonance image (MRI) and its deviation from chronological age can provide early insights into potential neurodegenerative diseases, supporting early detection and implementation of prev…
Age EstimationDiffusion MRIDisease PredictionThe shape of the brain's connections is predictive of cognitive performance: an explainable machine learning study
The shape of the brain's white matter connections is relatively unexplored in diffusion MRI tractography analysis. While it is known that tract shape varies in populations and across the human lifespan, it is unknown if …
Diffusion MRIParsing altered brain connectivity in neurodevelopmental disorders by integrating graph-based normative modeling and deep generative networks
Divergent brain connectivity is thought to underlie the behavioral and cognitive symptoms observed in many neurodevelopmental disorders. Quantifying divergence from neurotypical connectivity patterns offers a promising p…
Diffusion MRI