8 papers
Large-Scale Deployment and Analytical Implications of Structured Quality Control in Diffusion Magnetic Resonance Imaging
Michael E. Kim, Chenyu Gao, Karthik Ramadass +17
Purpose: Diffusion MRI (dMRI) provides a diverse set of quantitative measures and derived datatypes to assess white matter microstructure and macrostructure. Coupled with the incre…
ECLARE: Efficient cross-planar learning for anisotropic resolution enhancement
Samuel W. Remedios, Shuwen Wei, Shuo Han +6
In clinical imaging, magnetic resonance (MR) image volumes are often acquired as stacks of 2D slices with decreased scan times, improved signal-to-noise ratio, and image contrasts…
Likelihood-Separable Diffusion Inference for Multi-Image MRI Super-Resolution
Samuel W. Remedios, Zhangxing Bian, Shuwen Wei +3
Diffusion models are the current state-of-the-art for solving inverse problems in imaging. Their impressive generative capability allows them to approximate sampling from a prior d…
CATNUS: Coordinate-Aware Thalamic Nuclei Segmentation Using T1-Weighted MRI
Anqi Feng, Zhangxing Bian, Samuel W. Remedios +6
Accurate segmentation of thalamic nuclei from magnetic resonance images is important due to the distinct roles of these nuclei in overall brain function and to their differential i…
Synthetic multi-inversion time magnetic resonance images for visualization of subcortical structures
Savannah P. Hays, Lianrui Zuo, Anqi Feng +7
Purpose: Visualization of subcortical gray matter is essential in neuroscience and clinical practice, particularly for disease understanding and surgical planning.While multi-inver…
Diffusion-Driven Generation of Minimally Preprocessed Brain MRI
Samuel W. Remedios, Aaron Carass, Jerry L. Prince +1
The purpose of this study is to present and compare three denoising diffusion probabilistic models (DDPMs) that generate 3D -weighted MRI human brain images. Three DDPMs were…