Search Results for author: Christoph Großbröhmer

Found 2 papers, 1 papers with code

Chasing Clouds: Differentiable Volumetric Rasterisation of Point Clouds as a Highly Efficient and Accurate Loss for Large-Scale Deformable 3D Registration

1 code implementation • ICCV 2023 • Mattias P. Heinrich, Alexander Bigalke, Christoph Großbröhmer, Lasse Hansen

Learning-based registration for large-scale 3D point clouds has been shown to improve robustness and accuracy compared to classical methods and can be trained without supervision for locally rigid problems.

Self-Supervised Learning

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Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning

no code implementations • 8 Dec 2021 • Alessa Hering, Lasse Hansen, Tony C. W. Mok, Albert C. S. Chung, Hanna Siebert, Stephanie Häger, Annkristin Lange, Sven Kuckertz, Stefan Heldmann, Wei Shao, Sulaiman Vesal, Mirabela Rusu, Geoffrey Sonn, Théo Estienne, Maria Vakalopoulou, Luyi Han, Yunzhi Huang, Pew-Thian Yap, Mikael Brudfors, Yaël Balbastre, Samuel Joutard, Marc Modat, Gal Lifshitz, Dan Raviv, Jinxin Lv, Qiang Li, Vincent Jaouen, Dimitris Visvikis, Constance Fourcade, Mathieu Rubeaux, Wentao Pan, Zhe Xu, Bailiang Jian, Francesca De Benetti, Marek Wodzinski, Niklas Gunnarsson, Jens Sjölund, Daniel Grzech, Huaqi Qiu, Zeju Li, Alexander Thorley, Jinming Duan, Christoph Großbröhmer, Andrew Hoopes, Ingerid Reinertsen, Yiming Xiao, Bennett Landman, Yuankai Huo, Keelin Murphy, Nikolas Lessmann, Bram van Ginneken, Adrian V. Dalca, Mattias P. Heinrich

Image registration is a fundamental medical image analysis task, and a wide variety of approaches have been proposed.

Image Registration Medical Image Registration

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