1 citations · 1 across the 3 of their papers we have counts for
3 papers
The Surprising Effectiveness of Noise Pretraining for Implicit Neural Representations
Kushal Vyas, Alper Kayabasi, Daniel Kim +3
The approximation and convergence properties of implicit neural representations (INRs) are known to be highly sensitive to parameter initialization strategies. While several data-d…
ScarNet: A Novel Foundation Model for Automated Myocardial Scar Quantification from LGE in Cardiac MRI
Neda Tavakoli, Amir Ali Rahsepar, Brandon C. Benefield +9
Background: Late Gadolinium Enhancement (LGE) imaging is the gold standard for assessing myocardial fibrosis and scarring, with left ventricular (LV) LGE extent predicting major ad…
DRL-STNet: Unsupervised Domain Adaptation for Cross-modality Medical Image Segmentation via Disentangled Representation Learning
Hui Lin, Florian Schiffers, Santiago López-Tapia +3
Unsupervised domain adaptation (UDA) is essential for medical image segmentation, especially in cross-modality data scenarios. UDA aims to transfer knowledge from a labeled source…