most citedData-Driven Abdominal Phenotypes of Type 2 Diabetes in Lean, Overweight, and Obese Cohorts

1 citations · 1 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.CV2025

Lifespan Pancreas Morphology for Control vs Type 2 Diabetes using AI on Largescale Clinical Imaging

Lucas W. Remedios, Chloe Cho, Trent M. Schwartz +11

Purpose: Understanding how the pancreas changes is critical for detecting deviations in type 2 diabetes and other pancreatic disease. We measure pancreas size and shape using morph…

cs.CV20251 cited

Data-Driven Abdominal Phenotypes of Type 2 Diabetes in Lean, Overweight, and Obese Cohorts

Lucas W. Remedios, Chloe Cho, Trent M. Schwartz +10

Purpose: Although elevated BMI is a well-known risk factor for type 2 diabetes, the disease's presence in some lean adults and absence in others with obesity suggests that detailed…