Deep-learning-based registration methods emerged as a fast alternative to conventional
registration methods. However, these methods often still cannot achieve the same …

In the last two years learning-based methods have started to show encouraging results in
different supervised and unsupervised medical image registration tasks. Deep neural …

Many inverse problems are phrased as optimization problems in which the objective
function is the sum of a data-fidelity term and a regularization. Often, the Hessian of the …

Abstract 3D image registration is one of the most fundamental and computationally
expensive operations in medical image analysis. Here, we present a mixed-precision …

With this work we release CLAIRE, a distributed-memory implementation of an effective
solver for constrained large deformation diffeomorphic image registration problems in three …

In follow-up CT examinations of cancer patients, therapy success is evaluated by estimating
the change in tumor size. This process is time-consuming and error-prone. We present a …

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 coarse …

We study the performance of CLAIRE—a diffeomorphic multi-node, multi-GPU image-
registration algorithm and software—in large-scale biomedical imaging applications with …

Purpose Multimodal imaging plays a key role in patient assessment and treatment planning
in liver radioembolization. It will reach its full potential for convenient use in combination with …

We present a Gauss-Newton-Krylov solver for large deformation diffeomorphic image
registration. We extend the publicly available CLAIRE library to multi-node multi-graphics …