Advanced Neuroimaging Techniques and Applications

This study uses diffusion kurtosis imaging to detect microstructural changes in the temporal pole of TLE patients, showing differences between lesional and non-lesional groups and correlations with seizure duration.

DDMReg improves diffusion MRI registration by using whole-brain and tract-specific information, showing better performance across diverse datasets.

This study quantifies the prevalence of bottleneck regions in white matter where multiple fiber populations share the same orientation, showing over 50-70% of fixels are affected, leading to potential errors in tractography.

This paper maps the human corticoreticular pathway (CRP) using diffusion tractography and identifies its cortical origins, trajectory, and bilateral projections to the brainstem.

This paper introduces a robust tractogram filtering method that accounts for motion artefacts in diffusion MRI, validated with simulations and infant data, showing improved structural connectivity and microstructural analyses.

The paper uses high-resolution myelin mapping to show graded variation in cortical myelination rates along the sensorimotor-association axis during adolescence.

The paper uses restriction spectrum imaging to analyze age-related microstructural changes in brain diffusion across 9-14 year olds from the ABCD Study, finding increased restricted diffusion in subcortical regions with age.

This study uses ultra-strong gradient MRI to show that myelin changes, not axon density, are linked to premanifest Huntington's disease, with mutation size correlating with myelin levels.

This paper introduces a tissue-weighted mean method to reduce bias in NODDI metrics by accounting for CSF partial volume, showing it improves accuracy in ROI analysis for neurodegenerative disease studies.

This study uses non-negative matrix factorization to identify 5 spatially distinct striatal components in the human striatum, showing increased stability with multimodal data and associations with age and sex.

The paper maps subcortical regions in macaque brains using MAP-MRI and histology, creating a digital atlas for neuroanatomical studies.

The paper introduces mrHARDIflow, a pipeline for preprocessing and analyzing multi-resolution diffusion MRI data, and applies it to study variability in the PRIME-DE database.

This study evaluates the reliability of dMRI-based tractometry by assessing reproducibility, test-retest reliability, and robustness using software and datasets from the Human Connectome Project and clinical-grade measurements.

This study segments the human entorhinal cortex using structural connectivity, identifying MEC and LEC homologues based on differential connections to specific brain regions.

This study improves automated white-matter tractography in lower-quality diffusion MRI data by training on high-quality Connectom data and manually annotated pathways.

The paper evaluates powder averaging's effectiveness in diffusion MRI for axon diameter estimation in complex brain architectures, finding it accurate across parameters but sensitive to microdispersion at low b-values.

This study evaluates the test-retest reproducibility of OGSE and microA dMRI metrics in mice brains, finding high reproducibility for microA and Lambda but not OGSE.

This study compares Fixel-based analysis and free water corrected DTI metrics in HIV+ and HIV- individuals to assess white matter damage and its association with cognitive impairment.

This study compares diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) in UK Biobank data to assess how non-Gaussian diffusion metrics improve understanding of white matter aging.

This paper introduces a super-resolution reconstruction framework for diffusion MRI, showing it improves signal accuracy and precision in low-SNR conditions, especially with high-resolution and spherical b-tensor encoding.

PyDesigner is a Python package that preprocesses diffusion MRI data and estimates tensors, improving accuracy and robustness of diffusion and kurtosis metrics.

This paper reassesses WM-behaviour relationships using multimodal microstructural imaging in 50 healthy individuals, finding partial support for FA-behaviour links and suggesting multimodal approaches may better capture WM-behaviour associations.

The paper develops a combined MRI and light sheet imaging approach to generate high-resolution brain phenotypes for neurogenetic studies in mice.

The paper investigates how white matter connectivity scales with brain size across primate species, finding a bottleneck in connectivity in larger brains.

dStripe corrects slice artefacts in diffusion MRI using a constrained neural network to reduce interslice inconsistencies without biasing data.

This study validates compressed sensing for DSI reconstruction, showing high fidelity at R=3 with reduced acquisition time, but degradation at higher acceleration factors.

This study uses deep neural networks to accelerate parameter estimation in a high-dimensional diffusion-relaxation MRI model but finds that machine learning cannot replace careful acquisition protocol design.

This paper uses quantitative MRI to non-invasively map the human lateral geniculate nucleus and its subdivisions, showing that T1 contrast reflects cyto- and myeloarchitectonic differences.

This paper shows that training data distribution affects the accuracy and precision of microstructural parameter estimates using supervised machine learning in quantitative MRI.