Papers Diffusion MRI
“Diffusion MRI” 태그가 달린 논문 213편 · 필터 해제
Topological Learning for Brain Networks
This paper proposes a novel topological learning framework that integrates networks of different sizes and topology through persistent homology. Such challenging task is made possible through the introduction of a comput…
Diffusion MRILearning unbiased group-wise registration (LUGR) and joint segmentation: evaluation on longitudinal diffusion MRI
Analysis of longitudinal changes in imaging studies often involves both segmentation of structures of interest and registration of multiple timeframes. The accuracy of such analysis could benefit from a tailored framewor…
Diffusion MRIPatch2Self: Denoising Diffusion MRI with Self-Supervised Learning
Diffusion-weighted magnetic resonance imaging (DWI) is the only noninvasive method for quantifying microstructure and reconstructing white-matter pathways in the living human brain. Fluctuations from multiple sources cre…
DenoisingDiffusion MRIMedical DiagnosisSelf-Supervised LearningFiltering in tractography using autoencoders (FINTA)
Current brain white matter fiber tracking techniques show a number of problems, including: generating large proportions of streamlines that do not accurately describe the underlying anatomy; extracting streamlines that a…
AnatomyDiffusion MRIDomain AdaptationThe NonHuman Primate Neuroimaging & Neuroanatomy Project
Multi-modal neuroimaging projects are advancing our understanding of human brain architecture, function, connectivity using high-quality non-invasive data from many subjects. However, ground truth validation of connectiv…
Diffusion MRIFocal to bilateral tonic-clonic seizures are associated with widespread network abnormality in temporal lobe epilepsy
Objective: To identify if whole-brain structural network alterations in patients with temporal lobe epilepsy (TLE) and focal to bilateral tonic-clonic seizures (FBTCS) differ from alterations in patients without FBTCS. …
Diffusion MRIQ-space quantitative diffusion MRI measures using a stretched-exponential representation
Diffusion magnetic resonance imaging (dMRI) is a relatively modern technique used to study tissue microstructure in a non-invasive way. Non-Gaussian diffusion representation is related to the restricted diffusion and can…
Diffusion MRIPrognosisLearning Anatomical Segmentations for Tractography from Diffusion MRI
Deep learning approaches for diffusion MRI have so far focused primarily on voxel-based segmentation of lesions or white-matter fiber tracts. A drawback of representing tracts as volumetric labels, rather than sets of st…
Diffusion MRISegmentationTowards learned optimal q-space sampling in diffusion MRI
Fiber tractography is an important tool of computational neuroscience that enables reconstructing the spatial connectivity and organization of white matter of the brain. Fiber tractography takes advantage of diffusion Ma…
Diffusion MRIFeedback Graph Attention Convolutional Network for Medical Image Enhancement
Artifacts, blur and noise are the common distortions degrading MRI images during the acquisition process, and deep neural networks have been demonstrated to help in improving image quality. To well exploit global structu…
Diffusion MRIGraph AttentionGraph SimilarityImage Enhancement+2Neuro4Neuro: A neural network approach for neural tract segmentation using large-scale population-based diffusion imaging
Subtle changes in white matter (WM) microstructure have been associated with normal aging and neurodegeneration. To study these associations in more detail, it is highly important that the WM tracts can be accurately and…
Diffusion MRISegmentationTractometry-based Anomaly Detection for Single-subject White Matter Analysis
There is an urgent need for a paradigm shift from group-wise comparisons to individual diagnosis in diffusion MRI (dMRI) to enable the analysis of rare cases and clinically-heterogeneous groups. Deep autoencoders have sh…
Anomaly DetectionDiffusion MRIMachine Learning Methods for Brain Network Classification: Application to Autism Diagnosis using Cortical Morphological Networks
Autism spectrum disorder (ASD) affects the brain connectivity at different levels. Nonetheless, non-invasively distinguishing such effects using magnetic resonance imaging (MRI) remains very challenging to machine learni…
BenchmarkingBIG-bench Machine LearningDiagnosticDiffusion MRI+3Deep Cerebellar Nuclei Segmentation via Semi-Supervised Deep Context-Aware Learning from 7T Diffusion MRI
Deep cerebellar nuclei are a key structure of the cerebellum that are involved in processing motor and sensory information. It is thus a crucial step to accurately segment deep cerebellar nuclei for the understanding of …
Diffusion MRIPatient-Specific SegmentationSegmentationDiffusion MRI Consistent Wire Models for Efficient Solutions of the Anisotropic Forward Problem in Electroencephalography
The surface Boundary Element Method (BEM) is one of the most commonly employed formulations to solve the forward problem in electroencephalography, but the applicability of its classical incarnations is lamentably limite…
Diffusion MRIManifold-Aware CycleGAN for High-Resolution Structural-to-DTI Synthesis
Unpaired image-to-image translation has been applied successfully to natural images but has received very little attention for manifold-valued data such as in diffusion tensor imaging (DTI). The non-Euclidean nature of D…
Diffusion MRIImage-to-Image TranslationVocal Bursts Intensity PredictionThe Graph of Our Mind
Graph theory in the last two decades penetrated sociology, molecular biology, genetics, chemistry, computer engineering, and numerous other fields of science. One of the more recent areas of its applications is the study…
Diffusion MRISociologyMultifold Acceleration of Diffusion MRI via Slice-Interleaved Diffusion Encoding (SIDE)
Diffusion MRI (dMRI) is a unique imaging technique for in vivo characterization of tissue microstructure and white matter pathways. However, its relatively long acquisition time implies greater motion artifacts when imag…
Diffusion MRIUnderstanding Alzheimer disease’s structural connectivity through explainable AI
In the following work, we use a modified version of deep BrainNet convolutional neural network (CNN) trained on the diffusion weighted MRI (DW-MRI) tractography connectomes of patients with Alzheimer’s Disease (AD) and M…
Diffusion MRIModel-Based Deep Learning for Reconstruction of Joint k-q Under-sampled High Resolution Diffusion MRI
We propose a model-based deep learning architecture for the reconstruction of highly accelerated diffusion magnetic resonance imaging (MRI) that enables high resolution imaging. The proposed reconstruction jointly recove…
DenoisingDiffusion MRI