activity
20242026
most citedMICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2026

Personalized White Matter Bundle Segmentation for Early Childhood

Elyssa M. McMaster, Michael E. Kim, Nancy R. Newlin +12

White matter segmentation methods from diffusion magnetic resonance imaging range from streamline clustering-based approaches to bundle mask delineation, but none have proposed a p…

q-bio.NC2025

Characterizing Continuous and Discrete Hybrid Latent Spaces for Structural Connectomes

Gaurav Rudravaram, Lianrui Zuo, Adam M. Saunders +12

Structural connectomes are detailed graphs that map how different brain regions are physically connected, offering critical insight into aging, cognition, and neurodegenerative dis…

eess.IV2025

Fully Differentiable dMRI Streamline Propagation in PyTorch

Jongyeon Yoon, Elyssa M. McMaster, Michael E. Kim +4

Diffusion MRI (dMRI) provides a distinctive means to probe the microstructural architecture of living tissue, facilitating applications such as brain connectivity analysis, modelin…

cs.LG2025

Scale-up Unlearnable Examples Learning with High-Performance Computing

Yanfan Zhu, Issac Lyngaas, Murali Gopalakrishnan Meena +8

Recent advancements in AI models are structured to retain user interactions, which could inadvertently include sensitive healthcare data. In the healthcare field, particularly when…

physics.med-ph20242 cited

MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI

Nancy R. Newlin, Kurt Schilling, Serge Koudoro +33

White matter alterations are increasingly implicated in neurological diseases and their progression. International-scale studies use diffusion-weighted magnetic resonance imaging (…