Papers Diffusion MRI
“Diffusion MRI” 태그가 달린 논문 213편 · 필터 해제
Exploring the robustness of TractOracle methods in RL-based tractography
Tractography algorithms leverage diffusion MRI to reconstruct the fibrous architecture of the brain's white matter. Among machine learning approaches, reinforcement learning (RL) has emerged as a promising framework for …
Diffusion MRIreinforcement-learningReinforcement LearningReinforcement Learning (RL)Convergent and divergent connectivity patterns of the arcuate fasciculus in macaques and humans
The organization and connectivity of the arcuate fasciculus (AF) in nonhuman primates remain contentious, especially concerning how its anatomy diverges from that of humans. Here, we combined cross-scale single-neuron tr…
AnatomyDiffusion MRIBrainSymphony: A Transformer-Driven Fusion of fMRI Time Series and Structural Connectivity
Existing foundation models for neuroimaging are often prohibitively large and data-intensive. We introduce BrainSymphony, a lightweight, parameter-efficient foundation model that achieves state-of-the-art performance whi…
Diffusion MRINetwork IdentificationTime SeriesImplicit neural representations for accurate estimation of the standard model of white matter
Diffusion magnetic resonance imaging (dMRI) enables non-invasive investigation of tissue microstructure. The Standard Model (SM) of white matter aims to disentangle dMRI signal contributions from intra- and extra-axonal …
Diffusion MRIDeepMultiConnectome: Deep Multi-Task Prediction of Structural Connectomes Directly from Diffusion MRI Tractography
Diffusion MRI (dMRI) tractography enables in vivo mapping of brain structural connections, but traditional connectome generation is time-consuming and requires gray matter parcellation, posing challenges for large-scale …
Diffusion MRIMulti-Task LearningCross-Sequence Semi-Supervised Learning for Multi-Parametric MRI-Based Visual Pathway Delineation
Accurately delineating the visual pathway (VP) is crucial for understanding the human visual system and diagnosing related disorders. Exploring multi-parametric MR imaging data has been identified as an important way to …
Diffusion MRIEnhancing Diffusion-Weighted Images (DWI) for Diffusion MRI: Is it Enough without Non-Diffusion-Weighted B=0 Reference?
Diffusion MRI (dMRI) is essential for studying brain microstructure, but high-resolution imaging remains challenging due to the inherent trade-offs between acquisition time and signal-to-noise ratio (SNR). Conventional m…
Diffusion MRISuper-ResolutionComBAT Harmonization for diffusion MRI: Challenges and Best Practices
Over the years, ComBAT has become the standard method for harmonizing MRI-derived measurements, with its ability to compensate for site-related additive and multiplicative biases while preserving biological variability. …
Diffusion MRIAn Arbitrary-Modal Fusion Network for Volumetric Cranial Nerves Tract Segmentation
The segmentation of cranial nerves (CNs) tract provides a valuable quantitative tool for the analysis of the morphology and trajectory of individual CNs. Multimodal CNs tract segmentation networks, e.g., CNTSeg, which co…
Diffusion MRISegmentationA Multimodal Deep Learning Approach for White Matter Shape Prediction in Diffusion MRI Tractography
Shape measures have emerged as promising descriptors of white matter tractography, offering complementary insights into anatomical variability and associations with cognitive and clinical phenotypes. However, conventiona…
Diffusion MRIDimensionality ReductionMultimodal Deep LearningDual Deep Learning Approach for Non-invasive Renal Tumour Subtyping with VERDICT-MRI
This work aims to characterise renal tumour microstructure using diffusion MRI (dMRI); via the Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumours (VERDICT)-MRI framework with self-supervised learni…
Diffusion MRIfeature selectionSelf-Supervised LearningEquivariant Spherical CNNs for Accurate Fiber Orientation Distribution Estimation in Neonatal Diffusion MRI with Reduced Acquisition Time
Early and accurate assessment of brain microstructure using diffusion Magnetic Resonance Imaging (dMRI) is crucial for identifying neurodevelopmental disorders in neonates, but remains challenging due to low signal-to-no…
DiagnosticDiffusion MRIDeepNuParc: A Novel Deep Clustering Framework for Fine-scale Parcellation of Brain Nuclei Using Diffusion MRI Tractography
Brain nuclei are clusters of anatomically distinct neurons that serve as important hubs for processing and relaying information in various neural circuits. Fine-scale parcellation of the brain nuclei is vital for a compr…
ClusteringDeep ClusteringDiffusion MRIDimensionality ReductionGlobal Context Is All You Need for Parallel Efficient Tractography Parcellation
Whole-brain tractography in diffusion MRI is often followed by a parcellation in which each streamline is classified as belonging to a specific white matter bundle, or discarded as a false positive. Efficient parcellatio…
AllData AugmentationDiffusion MRIGPUDeep Learning-Based Diffusion MRI Tractography: Integrating Spatial and Anatomical Information
Diffusion MRI tractography technique enables non-invasive visualization of the white matter pathways in the brain. It plays a crucial role in neuroscience and clinical fields by facilitating the study of brain connectivi…
Diffusion MRIDDCSR: A Novel End-to-End Deep Learning Framework for Cortical Surface Reconstruction from Diffusion MRI
Diffusion MRI (dMRI) plays a crucial role in studying brain white matter connectivity. Cortical surface reconstruction (CSR), including the inner whiter matter (WM) and outer pial surfaces, is one of the key tasks in dMR…
Diffusion MRISurface ReconstructionA Novel Streamline-based diffusion MRI Tractography Registration Method with Probabilistic Keypoint Detection
Registration of diffusion MRI tractography is an essential step for analyzing group similarities and variations in the brain's white matter (WM). Streamline-based registration approaches can leverage the 3D geometric inf…
Diffusion MRIKeypoint DetectionMicroscopic Propagator Imaging (MPI) with Diffusion MRI
We propose Microscopic Propagator Imaging (MPI) as a novel method to retrieve the indices of the microscopic propagator which is the probability density function of water displacements due to diffusion within the nervous…
Diffusion MRIReMiDi: Reconstruction of Microstructure Using a Differentiable Diffusion MRI Simulator
We propose ReMiDi, a novel method for inferring neuronal microstructure as arbitrary 3D meshes using a differentiable diffusion Magnetic Resonance Imaging (dMRI) simulator. We first implemented in PyTorch a differentiabl…
Diffusion MRIFetDTIAlign: A Deep Learning Framework for Affine and Deformable Registration of Fetal Brain dMRI
Diffusion MRI (dMRI) provides unique insights into fetal brain microstructure in utero. Longitudinal and cross-sectional fetal dMRI studies can reveal crucial neurodevelopmental changes but require precise spatial alignm…
Deep LearningDiffusion MRI