12 citations · 17 across the 3 of their papers we have counts for
6 papers · 1 filter
CNN-based Lung CT Registration with Multiple Anatomical Constraints
Alessa Hering, Stephanie Häger, Jan Moltz +3
Deep-learning-based registration methods emerged as a fast alternative to conventional registration methods. However, these methods often still cannot achieve the same performance…
Deformable Groupwise Image Registration using Low-Rank and Sparse Decomposition
Roland Haase, Stefan Heldmann, Jan Lellmann
Low-rank and sparse decompositions and robust PCA (RPCA) are highly successful techniques in image processing and have recently found use in groupwise image registration. In this p…
mlVIRNET: Multilevel Variational Image Registration Network
Alessa Hering, Bram van Ginneken, Stefan Heldmann
We present a novel multilevel approach for deep learning based image registration. Recently published deep learning based registration methods have shown promising results for a wi…
Robust, fast and accurate: a 3-step method for automatic histological image registration
Johannes Lotz, Nick Weiss, Stefan Heldmann
We present a 3-step registration pipeline for differently stained histological serial sections that consists of 1) a robust pre-alignment, 2) a parametric registration computed on…
Enhancing Label-Driven Deep Deformable Image Registration with Local Distance Metrics for State-of-the-Art Cardiac Motion Tracking
Alessa Hering, Sven Kuckertz, Stefan Heldmann +1
While deep learning has achieved significant advances in accuracy for medical image segmentation, its benefits for deformable image registration have so far remained limited to red…
Estimation of Large Motion in Lung CT by Integrating Regularized Keypoint Correspondences into Dense Deformable Registration
Jan Rühaak, Thomas Polzin, Stefan Heldmann +4
We present a novel algorithm for the registration of pulmonary CT scans. Our method is designed for large respiratory motion by integrating sparse keypoint correspondences into a d…