2 papers
eess.IV2025
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…
cs.CV2025
Progressive Test Time Energy Adaptation for Medical Image Segmentation
Xiaoran Zhang, Byung-Woo Hong, Hyoungseob Park +5
We propose a model-agnostic, progressive test-time energy adaptation approach for medical image segmentation. Maintaining model performance across diverse medical datasets is chall…