Nov 25, 2019 · In this paper, we employ Bayesian deep learning in order to register the medical images that are corrupted by nonlinear geometric distortions.

Feb 26, 2021 · Deformable image registration is one of the challenging inverse problems in medical images due to inevitable geometric distortions during ...

Given a pair of reference and moving image, our objective is to register the moving image onto the reference image coordinates while maintaining the pixel ...

Aug 10, 2020 · We introduce a fully Bayesian framework for unsupervised DL-based deformable image registration. Our method provides a principled way to characterize the true ...

In this paper, we attempt to give an overview of deformable registration methods, putting emphasis on the most recent advances in the domain.

Deformable image registration is one of the challenging inverse problems in medical images due to inevitable geometric distortions during the imaging.

Oct 25, 2024 · This paper proposes a novel framework integrating Bayesian optimization to address these challenges, focusing on registering 3D point clouds representing brain ...

We introduce NPBDREG, a fully non-parametric Bayesian framework for uncertainty estimation in DNN-based deformable image registration.

Deep learning-based medical image registration can be primarily categorized into deep iterative registration, supervised, and unsupervised transformation ...

We propose an interpretable Bayesian framework (BayeSeg) through Bayesian modeling of image and label statistics to enhance model generalizability for medical ...