no code implementations • 8 Mar 2024 • Junyu Chen, Yihao Liu, Shuwen Wei, Zhangxing Bian, Aaron Carass, Yong Du
Here, we propose a novel framework to concurrently estimate both the epistemic and aleatoric segmentation uncertainties for image registration.
no code implementations • 31 Jan 2024 • Zhangxing Bian, Ahmed Alshareef, Shuwen Wei, Junyu Chen, Yuli Wang, Jonghye Woo, Dzung L. Pham, Jiachen Zhuo, Aaron Carass, Jerry L. Prince
This is a factor that has been overlooked in prior research on tMRI post-processing.
no code implementations • 5 Aug 2023 • Zhangxing Bian, Shuwen Wei, Yihao Liu, Junyu Chen, Jiachen Zhuo, Fangxu Xing, Jonghye Woo, Aaron Carass, Jerry L. Prince
We introduce a novel "momenta, shooting, and correction" framework for Lagrangian motion estimation in the presence of repetitive patterns and large motion.
no code implementations • 28 Jul 2023 • Junyu Chen, Yihao Liu, Shuwen Wei, Zhangxing Bian, Shalini Subramanian, Aaron Carass, Jerry L. Prince, Yong Du
Deep learning technologies have dramatically reshaped the field of medical image registration over the past decade.
1 code implementation • 12 Dec 2022 • Yihao Liu, Junyu Chen, Shuwen Wei, Aaron Carass, Jerry Prince
For digital transformations, |J| is commonly approximated using a central difference, but this strategy can yield positive |J|'s for transformations that are clearly not diffeomorphic -- even at the voxel resolution level.