8 papers
IntraStyler: Intra-Domain Style Synthesis for Cross-Modality MRI Domain Adaptation
Han Liu, Yubo Fan, Hao Li +5
Segmentation of vestibular schwannoma and cochlea from T2 MRI is clinically important yet annotation-intensive. Domain adaptation (DA) has been widely adopted to bridge the gap bet…
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…
Harmonization mitigates diffusion MRI scanner effects in infancy: insights from the HEALthy Brain and Childhood Development (HBCD) study
Elyssa M. McMaster, Gaurav Rudravaram, Michael E. Kim +17
The HEALthy Brain and Childhood Development (HBCD) Study is an ongoing longitudinal initiative to understand population-level brain maturation; however, large-scale studies must ov…
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…
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…
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…