Susie Y. Huang

The paper compares four gray matter biophysical models on a public dataset, finding consistent parameter estimates and highlighting trade-offs in model complexity and robustness.

This paper uses HiP-CT to image microstructural fiber orientations in the human brain, showing greater complexity than dMRI while being non-destructive.

This paper presents the first extensive reconstruction of human subcortical fiber pathways using ultra-high-resolution dMRI, providing a high-definition atlas with clinical applications.

This paper presents high-resolution diffusion MRI data from macaque and human brains, enabling detailed mapping of axonal architecture and microstructure.

This study evaluates how diffusion MRI spatial resolution affects short-range association fiber reconstruction and structural connectivity estimation, finding that higher resolution and specific tractography methods improve accuracy.

This study uses diffusion MRI and a new model to identify distinct cellular processes underlying motor skill learning in the human brain.

This paper demonstrates in vivo human brain neurite exchange imaging using a high-gradient MRI scanner, showing faster exchange times and spatial variation across cortical regions.

This paper introduces Romer-EPTI, a novel dMRI technique that improves SNR, motion robustness, and image quality for in-vivo mesoscale imaging.

This study validates the Gaussian diffusion model at the mesoscopic scale in live human brain tissue using diffusion tensor distribution MRI.

This study quantifies how axonal beading and undulation affect axon diameter estimation in diffusion MRI, showing potential biases up to 100% in pathological conditions.

This paper estimates axial diffusivity in the NODDI model using high b-value data and shows the impact of noise assumptions on parameter estimates.

This paper introduces HDnGAN, a hybrid denoising GAN that improves the quality of fast volumetric MRI by denoising Wave-CAIPI images, achieving better SNR, sharpness, and lesion conspicuity than existing methods.

This paper introduces a structured low-rank matrix modeling method to correct ghosting in ex vivo dMRI, improving accuracy and reliability of diffusion metrics.

The paper presents a high-resolution in vivo whole-brain diffusion MRI dataset with detailed anatomical images and field maps for research and development of dMRI techniques.