Lauren J. O’Donnell

ROVER-dMRI improves high-SNR whole-brain mesoscale diffusion MRI with reduced scan time and preserved fiber details.

This study evaluates whether cross-population white matter atlases improve test-retest reproducibility compared to single-population atlases in diffusion MRI tractography.

This study systematically evaluates U-fiber organization in the rhesus monkey brain using tract tracing, revealing sulcus-dependent prevalence and diverse trajectories, challenging the notion of a uniform U-fiber system.

This paper develops a deep learning method to map white matter tracts from CT scans in intracerebral hemorrhage patients, showing high anatomical plausibility and correlation with motor scores.

ACCURAT provides an open framework and neuroanatomical reference for reconstructing cerebellar pathways using diffusion MRI and anatomical priors.

This study identifies sex differences in white matter tracts using diffusion MRI tractography and finds associations with motor function in a large cohort.

This study evaluates diffusion MRI contrasts for cerebellar segmentation, finding that spherical mean images outperform traditional microstructure maps.

This study examines the role of superficial white matter connections of Broca's area in language performance across children and adults, finding bilateral associations with language tasks.

This study examines cerebellar pathway microstructure and cognitive performance in over 9,000 participants, finding consistent associations across pre-adolescents and young adults.

This paper introduces FMQ Regression to analyze white matter microstructure and its relationship to cognitive and motor factors, finding stronger associations in bundle periphery and sex-specific differences.

This paper introduces DeepRGVP, a deep learning framework for automatically identifying the retinogeniculate visual pathway from diffusion MRI tractography data, showing superior performance compared to existing methods.

The paper harmonizes diffusion MRI data from the ABCD study and provides white matter measures for structural connectivity research in adolescents.

This study investigates the role of superficial white matter microstructure in processing speed in cerebral small vessel disease, finding that free-water measures in SWM strongly correlate with cognitive decline.

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

This study evaluates variability in white matter bundle segmentation across 42 groups using the same dataset, finding protocol variability exceeds other sources of inconsistency.

This study compares four tractography methods for reconstructing the retinogeniculate visual pathway using diffusion MRI data from 57 subjects, finding that UKF-2T and iFOD1 provide the best results.

This paper develops a deep learning method to segment brain tissue from diffusion MRI without anatomical registration, achieving high accuracy on both HCP and clinical data.

This paper creates a novel trigeminal tractography atlas for automated trigeminal nerve identification using dMRI data, showing comparable results to manual methods with advantages in efficiency and robustness.

This study creates a detailed 3D map of the human brainstem using high-resolution MRI and validates it against histological atlases.

This study uses diffusion MRI tractography to map individual variations of the human corticospinal tract and hand-related motor fibers, creating a database of their volume, length, and biophysical parameters.