3 papers
cs.CV2025
Using Foundation Models as Pseudo-Label Generators for Pre-Clinical 4D Cardiac CT Segmentation
Anne-Marie Rickmann, Stephanie L. Thorn, Shawn S. Ahn +9
Cardiac image segmentation is an important step in many cardiac image analysis and modeling tasks such as motion tracking or simulations of cardiac mechanics. While deep learning h…
eess.IV2023
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…
eess.IV2022
Learning correspondences of cardiac motion from images using biomechanics-informed modeling
Xiaoran Zhang, Chenyu You, Shawn Ahn +3
Learning spatial-temporal correspondences in cardiac motion from images is important for understanding the underlying dynamics of cardiac anatomical structures. Many methods explic…