collaborators

10 papers

eess.IV2026

Harmonizing MR Images Across 100+ Scanners: Multi-site Validation with Traveling Subjects and Real-world Protocols

Savannah P. Hays, Lianrui Zuo, Muhammad Faizyab Ali Chaudhary +13

Reliable harmonization of heterogeneous magnetic resonance~(MR) image datasets, especially those acquired in pragmatic clinical trials, is critical to advance multi-center neuroima…

cs.CV2026

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…

eess.IV2026

Solving a Nonlinear Blind Inverse Problem for Tagged MRI with Physics and Deep Generative Priors

Zhangxing Bian, Shuwen Wei, Samuel W. Remedios +4

Tagged MRI enables tracking internal tissue motion non-invasively. It encodes motion by modulating anatomy with periodic tags, which deform along with tissue. However, the entangle…

cs.CV2026

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…

eess.IV2025

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…

eess.IV2025

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…