Description
Book Synopsis- Super-Resolution of Diffusion-Weighted Images via TDI-Conditioned Diffusion Model.
.- Diffusion-Based Gray-White Matter Mapping for Quantitative Tractography in Glioma Patients.
.- Ground-truth effects in learning-based fiber orientation distribution estimation in neonatal brains.
.- Synthesizing 3D axon morphology: springs are all we need.
.- Randomly COMMITting: Iterative Convex Optimization for Microstructure-Informed Tractography.
.- AID-DTI: Accelerating High-fidelity Diffusion Tensor Imaging with Detail-preserving Model-based Deep Learning.
.- Multi-dimensional Parameter Space Exploration for Streamline-specific Tractography.
.- Cross-domain Fiber Cluster Shape Analysis for Language Performance Cognitive Score Prediction.
.- Can Transfer Learning Improve Supervised Segmentation of White Matter Bundles in Glioma Patients.
.- Image Quality Transfer of Diffusion MRI Guided By High-Resolution Structural MRI.
.- QID2: An Image-Conditioned Diffusion Model for Q-space Up-sampling of DWI Data.
.- Ts-FWE: Token-Aware Single-shell Free Water Estimation for Brain Diffusion MRI.
.- Assessing Early Motor System Degeneration in the Spinal Cord of ALS Patients Using Diffusion MRI: An Exploratory Study.
.- RobNODDI: Robust NODDI Parameter Estimation with Adaptive Sampling under Continuous Representation.
.- Introducing QuantConn: Overcoming challenging diffusion acquisitions with harmonization.
.- Learning Low-Rank Tensor Approximation for GPU-based Tractography.
.- Deep multivariate autoencoder for capturing complexity in Brain Structure and Behaviour Relationships.
.- Heritability and Genetic Correlations Along the Corticospinal Tract.
.- Corpus Callosum Parcellation Methods: What Can Tractography Tell Us About Them?.
