3 citations · 4 across the 5 of their papers we have counts for
3 papers · 1 filter
Snap-and-tune: combining deep learning and test-time optimization for high-fidelity cardiovascular volumetric meshing
Daniel H. Pak, Shubh Thaker, Kyle Baylous +3
High-quality volumetric meshing from medical images is a key bottleneck for physics-based simulations in personalized medicine. For volumetric meshing of complex medical structures…
Heteroscedastic Uncertainty Estimation Framework for Unsupervised Registration
Xiaoran Zhang, Daniel H. Pak, Shawn S. Ahn +6
Deep learning methods for unsupervised registration often rely on objectives that assume a uniform noise level across the spatial domain (e.g. mean-squared error loss), but noise d…
Holistic Multi-Slice Framework for Dynamic Simultaneous Multi-Slice MRI Reconstruction
Daniel H. Pak, Xiao Chen, Eric Z. Chen +3
Dynamic Magnetic Resonance Imaging (dMRI) is widely used to assess various cardiac conditions such as cardiac motion and blood flow. To accelerate MR acquisition, techniques such a…