Papers Diffusion MRI
“Diffusion MRI” 태그가 달린 논문 213편 · 필터 해제
Fitting a Directional Microstructure Model to Diffusion-Relaxation MRI Data with Self-Supervised Machine Learning
Machine learning is a powerful approach for fitting microstructural models to diffusion MRI data. Early machine learning microstructure imaging implementations trained regressors to estimate model parameters in a supervi…
Diffusion MRIparameter estimationSelf-Supervised LearningMicrostructure estimation from diffusion-MRI: Compartmentalized models in permeable cellular tissue
Diffusion-weighted magnetic resonance imaging (DW-MRI) is used to characterize brain tissue microstructure employing tissue-specific biophysical models. A current limitation, however, is that most of the proposed models …
Diffusion MRISlice estimation in diffusion MRI of neonatal and fetal brains in image and spherical harmonics domains using autoencoders
Diffusion MRI (dMRI) of the developing brain can provide valuable insights into the white matter development. However, slice thickness in fetal dMRI is typically high (i.e., 3-5 mm) to freeze the in-plane motion, which r…
AnatomyDiffusion MRIConstrained self-supervised method with temporal ensembling for fiber bundle detection on anatomic tracing data
Anatomic tracing data provides detailed information on brain circuitry essential for addressing some of the common errors in diffusion MRI tractography. However, automated detection of fiber bundles on tracing data is ch…
AnatomyDiffusion MRIA New Approach in MRI Signal Processing for Detecting the Axonal Organization of the Brain
This article introduces a new methodology for reconstructing the white matter fiber pathways of brain in diffusion MRI. Usually, the signal intensity values will be lesser in the direction of higher diffusivity. The prop…
Diffusion MRISuperficial White Matter Analysis: An Efficient Point-cloud-based Deep Learning Framework with Supervised Contrastive Learning for Consistent Tractography Parcellation across Populations and dMRI Acquisitions
Diffusion MRI tractography is an advanced imaging technique that enables in vivo mapping of the brain's white matter connections. White matter parcellation classifies tractography streamlines into clusters or anatomicall…
Contrastive LearningDiffusion MRIRoot-Cause Analysis of Activation Cascade Differences in Brain Networks
Diffusion MRI imaging and tractography algorithms have enabled the mapping of the macro-scale connectome of the entire brain. At the functional level, probably the simplest way to study the dynamics of macro-scale brain …
Diffusion MRIWhite Matter Tracts are Point Clouds: Neuropsychological Score Prediction and Critical Region Localization via Geometric Deep Learning
White matter tract microstructure has been shown to influence neuropsychological scores of cognitive performance. However, prediction of these scores from white matter tract data has not been attempted. In this paper, we…
Diffusion MRIPredictionTractoFormer: A Novel Fiber-level Whole Brain Tractography Analysis Framework Using Spectral Embedding and Vision Transformers
Diffusion MRI tractography is an advanced imaging technique for quantitative mapping of the brain's structural connectivity. Whole brain tractography (WBT) data contains over hundreds of thousands of individual fiber str…
Data AugmentationDiffusion MRIEnsemble LearningHow can spherical CNNs benefit ML-based diffusion MRI parameter estimation?
This paper demonstrates spherical convolutional neural networks (S-CNN) offer distinct advantages over conventional fully-connected networks (FCN) at estimating scalar parameters of tissue microstructure from diffusion M…
Diffusion MRIparameter estimationCombining Image Space and q-Space PDEs for Lossless Compression of Diffusion MR Images
Diffusion MRI is a modern neuroimaging modality with a unique ability to acquire microstructural information by measuring water self-diffusion at the voxel level. However, it generates huge amounts of data, resulting fro…
Diffusion MRIA microstructure estimation Transformer inspired by sparse representation for diffusion MRI
Diffusion magnetic resonance imaging (dMRI) is an important tool in characterizing tissue microstructure based on biophysical models, which are complex and highly non-linear. Resolving microstructures with optimization t…
Diffusion MRIInductive BiasIntracranial EEG structure-function coupling predicts surgical outcomes in focal epilepsy
Alterations to structural and functional brain networks have been reported across many neurological conditions. However, the relationship between structure and function -- their coupling -- is relatively unexplored, part…
Diffusion MRIEEGElectroencephalogram (EEG)Angular Super-Resolution in Diffusion MRI with a 3D Recurrent Convolutional Autoencoder
High resolution diffusion MRI (dMRI) data is often constrained by limited scanning time in clinical settings, thus restricting the use of downstream analysis techniques that would otherwise be available. In this work we …
Diffusion MRISuper-ResolutionMulti-modal learning for predicting the genotype of glioma
The isocitrate dehydrogenase (IDH) gene mutation is an essential biomarker for the diagnosis and prognosis of glioma. It is promising to better predict glioma genotype by integrating focal tumor image and geometric featu…
Clinical KnowledgeDiffusion MRIPrognosisPredicting conversion of mild cognitive impairment to Alzheimer's disease
Alzheimer's disease (AD) is the most common age-related dementia. Mild cognitive impairment (MCI) is the early stage of cognitive decline before AD. It is crucial to predict the MCI-to-AD conversion for precise managemen…
Contrastive LearningDiffusion MRIDiversityManagementNUQ: A Noise Metric for Diffusion MRI via Uncertainty Discrepancy Quantification
Diffusion MRI (dMRI) is the only non-invasive technique sensitive to tissue micro-architecture, which can, in turn, be used to reconstruct tissue microstructure and white matter pathways. The accuracy of such tasks is ha…
DenoisingDiffusion MRIUncertainty QuantificationParameter estimation for WMTI-Watson model of white matter using encoder-decoder recurrent neural network
Biophysical modelling of the diffusion MRI signal provides estimates of specific microstructural tissue properties. Although nonlinear optimization such as non-linear least squares (NLLS) is the most widespread method fo…
DecoderDiffusion MRIparameter estimationModel and predict age and sex in healthy subjects using brain white matter features: A deep learning approach
The human brain's white matter (WM) structure is of immense interest to the scientific community. Diffusion MRI gives a powerful tool to describe the brain WM structure noninvasively. To potentially enable monitoring of …
Diffusion MRIDiffusion Tensor Estimation with Uncertainty Calibration
It is highly desirable to know how uncertain a model's predictions are, especially for models that are complex and hard to understand as in deep learning. Although there has been a growing interest in using deep learning…
Deep LearningDiffusion MRI