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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…

eess.IV2025

Multipath cycleGAN for harmonization of paired and unpaired low-dose lung computed tomography reconstruction kernels

Aravind R. Krishnan, Thomas Z. Li, Lucas W. Remedios +12

Reconstruction kernels in computed tomography (CT) affect spatial resolution and noise characteristics, introducing systematic variability in quantitative imaging measurements such…