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 Analysis +1

Deformable image registration with deep network priors: a study on longitudinal PET images

no code implementations • 22 Nov 2021 • Constance Fourcade, Ludovic Ferrer, Noemie Moreau, Gianmarco Santini, Aishlinn Brennan, Caroline Rousseau, Marie Lacombe, Vincent Fleury, Mathilde Colombié, Pascal Jézéquel, Mario Campone, Mathieu Rubeaux, Diana Mateus

Inspired by Deep Image Prior, this paper introduces a different use of deep architectures as regularizers to tackle the image registration question.

Deep Learning Image Registration