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

1 citations · 1 across the 11 of their papers we have counts for

collaborators

13 papers

eess.IV2026

Separating mixtures of single-fiber orientation distributions for increased sensitivity to crossing white matter fibers

Adam M. Saunders, Gaurav Rudravaram, Michael E. Kim +10

Intro: Diffusion MRI allows for in vivo probing of brain tissue architecture via micron-level diffusion aggregated at the millimeter scale, but crossing white matter fibers decreas…

cs.AI2026

Generalizable field of view extension for diffusion MRI via conditional flow matching

Gaurav Rudravaram, Lianrui Zuo, Ema Topolnjak +22

Incomplete field-of-view (FOV) diffusion MRI (dMRI) acquisitions compromise whole-brain white matter analysis by excluding brain regions from tractography and connectivity studies.…

cs.CV2026

SliceBridge: Context-Consistent Repair of Corrupted Slice Intervals in T1-Weighted MRI

Jiheng Li, Michael E. Kim, Trent M. Schwartz +8

Structural magnetic resonance imaging (MRI) images are sometimes corrupted over a contiguous set of slices, where acquisition, motion, hardware, or reconstruction effects leave a s…

cs.LG2026

Unsupervised learning of acquisition variability in structural connectomes via hybrid latent space modeling

Gaurav Rudravaram, Lianrui Zuo, Karthik Ramadass +17

Acquisition differences across sites, scanners, and protocols in dMRI introduce variability that complicates structural connectome analysis. This motivates deep learning models tha…

eess.IV2026

Evaluation of neuroCombat and deep learning harmonization for multi-site magnetic resonance neuroimaging in youth with prenatal alcohol exposure

Chloe Scholten, Elyssa M. McMaster, Adam M. Saunders +8

In cases of prevalent diseases and disorders, such as Prenatal Alcohol Exposure (PAE), multi-site data collection allows for increased study samples. However, multi-site studies in…

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…

eess.IV2025

Quality assurance of the Federal Interagency Traumatic Brain Injury Research (FITBIR) database for multi-site MRI analysis

Adam M. Saunders, Michael E. Kim, Gaurav Rudravaram +8

The Federal Interagency Traumatic Brain Injury Research (FITBIR) database is a centralized data repository for traumatic brain injury (TBI) research. It includes over 45,529 magnet…

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…

eess.IV2025

DeepFixel: Crossing white matter fiber identification through spherical convolutional neural networks

Adam M. Saunders, Lucas W. Remedios, Elyssa M. McMaster +6

Diffusion-weighted magnetic resonance imaging allows for reconstruction of models for structural connectivity in the brain, such as fiber orientation distribution functions (ODFs)…

q-bio.QM2025

Phenotype discovery of traumatic brain injury segmentations from heterogeneous multi-site data

Adam M. Saunders, Michael E. Kim, Gaurav Rudravaram +8

Traumatic brain injury (TBI) is intrinsically heterogeneous, and typical clinical outcome measures like the Glasgow Coma Scale complicate this diversity. The large variability in s…

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.CV2025★ 1 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…