Papers Diffusion MRI
“Diffusion MRI” 태그가 달린 논문 213편 · 필터 해제
Domain-agnostic segmentation of thalamic nuclei from joint structural and diffusion MRI
The human thalamus is a highly connected subcortical grey-matter structure within the brain. It comprises dozens of nuclei with different function and connectivity, which are affected differently by disease. For this rea…
Diffusion MRISegmentation$E(3) \times SO(3)$-Equivariant Networks for Spherical Deconvolution in Diffusion MRI
We present Roto-Translation Equivariant Spherical Deconvolution (RT-ESD), an $E(3)\times SO(3)$ equivariant framework for sparse deconvolution of volumes where each voxel contains a spherical signal. Such 6D data natural…
Diffusion MRIDrDisco: Deep Registration for Distortion Correction of Diffusion MRI with single phase-encoding
Diffusion-weighted magnetic resonance imaging (DW-MRI) is a non-invasive way of imaging white matter tracts in the human brain. DW-MRIs are usually acquired using echo-planar imaging (EPI) with high gradient fields, whic…
Diffusion MRIdistortion correctionA Unified Learning Model for Estimating Fiber Orientation Distribution Functions on Heterogeneous Multi-shell Diffusion-weighted MRI
Diffusion-weighted (DW) MRI measures the direction and scale of the local diffusion process in every voxel through its spectrum in q-space, typically acquired in one or more shells. Recent developments in micro-structure…
Diffusion MRICellular EXchange Imaging (CEXI): Evaluation of a diffusion model including water exchange in cells using numerical phantoms of permeable spheres
Purpose: Biophysical models of diffusion MRI have been developed to characterize microstructure in various tissues, but existing models are not suitable for tissue composed of permeable spherical cells. In this study we …
Diffusion MRIFiber Tract Shape Measures Inform Prediction of Non-Imaging Phenotypes
Neuroimaging measures of the brain's white matter connections can enable the prediction of non-imaging phenotypes, such as demographic and cognitive measures. Existing works have investigated traditional microstructure a…
Diffusion MRIPredictionGenerative AI for Rapid Diffusion MRI with Improved Image Quality, Reliability and Generalizability
Diffusion MRI is a non-invasive, in-vivo biomedical imaging method for mapping tissue microstructure. Applications include structural connectivity imaging of the human brain and detecting microstructural neural changes. …
DenoisingDiffusion MRISuper-ResolutionResolving quantitative MRI model degeneracy with machine learning via training data distribution design
Quantitative MRI (qMRI) aims to map tissue properties non-invasively via models that relate these unknown quantities to measured MRI signals. Estimating these unknowns, which has traditionally required model fitting - an…
Diffusion MRIparameter estimationQuantitative MRIEstablishing group-level brain structural connectivity incorporating anatomical knowledge under latent space modeling
Brain structural connectivity, capturing the white matter fiber tracts among brain regions inferred by diffusion MRI (dMRI), provides a unique characterization of brain anatomical organization. One fundamental question t…
Diffusion MRIDDM$^2$: 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 in increased costs and patient discomfor…
DenoisingDiffusion MRITractGraphCNN: anatomically informed graph CNN for classification using diffusion MRI tractography
The structure and variability of the brain's connections can be investigated via prediction of non-imaging phenotypes using neural networks. However, known neuroanatomical relationships between input features are general…
Diffusion MRIMotion-Invariant Variational Auto-Encoding of Brain Structural Connectomes
Mapping of human brain structural connectomes via diffusion MRI offers a unique opportunity to understand brain structural connectivity and relate it to various human traits, such as cognition. However, head displacement…
Diffusion MRIRobust Circuitry-Based Scores of Structural Importance of Human Brain Areas
We consider the 1015-vertex human consensus connectome computed from the diffusion MRI data of 1064 subjects. We define seven different orders on these 1015 graph vertices, where the orders depend on parameters derived f…
AnatomyDiffusion MRITractography-Based Parcellation of Cerebellar Dentate Nuclei via a Deep Nonnegative Matrix Factorization Clustering Method
As the largest human cerebellar nucleus, the dentate nucleus (DN) functions significantly in the communication between the cerebellum and the rest of the brain. Structural connectivity-based parcellation has the potentia…
ClusteringDiffusion MRISpherical convolutional neural networks can improve brain microstructure estimation from diffusion MRI data
Diffusion magnetic resonance imaging is sensitive to the microstructural properties of brain tissue. However, estimating clinically and scientifically relevant microstructural properties from the measured signals remains…
Diffusion MRIparameter estimationHarmonization Benchmarking Tool for Neuroimaging Datasets
A major data pre-processing step for large, multi-site studies is to handle site effects by harmonizing data, generating a dataset that enables more powerful analyses and more robust algorithms. There is a wide variety o…
BenchmarkingDiffusion MRIDeepRGVP: A Novel Microstructure-Informed Supervised Contrastive Learning Framework for Automated Identification Of The Retinogeniculate Pathway Using dMRI Tractography
The retinogeniculate pathway (RGVP) is responsible for carrying visual information from the retina to the lateral geniculate nucleus. Identification and visualization of the RGVP are important in studying the anatomy of …
AnatomyContrastive LearningData AugmentationDiffusion MRIAngular upsampling in diffusion MRI using contextual HemiHex sub-sampling in q-space
Artificial Intelligence (Deep Learning(DL)/ Machine Learning(ML)) techniques are widely being used to address and overcome all kinds of ill-posed problems in medical imaging which was or in fact is seemingly impossible. …
Diffusion MRIregressionPhysics-informed Deep Diffusion MRI Reconstruction with Synthetic Data: Break Training Data Bottleneck in Artificial Intelligence
Diffusion magnetic resonance imaging (MRI) is the only imaging modality for non-invasive movement detection of in vivo water molecules, with significant clinical and research applications. Diffusion weighted imaging (DWI…
Deep LearningDiffusion MRIMRI ReconstructionTractoSCR: A Novel Supervised Contrastive Regression Framework for Prediction of Neurocognitive Measures Using Multi-Site Harmonized Diffusion MRI Tractography
Neuroimaging-based prediction of neurocognitive measures is valuable for studying how the brain's structure relates to cognitive function. However, the accuracy of prediction using popular linear regression models is rel…
Contrastive LearningDiffusion MRIFeature ImportancePrediction+2