• Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning 

      Hering, Alessa; Hansen, Lasse; Mok, Tony C. W.; Chung, Albert C. S.; Siebert, Hanna; Häger, Stephanie; Lange, Annkristin; Kuckertz, Sven; Heldmann, Stefan; Shao, Wei; Vesal, Sulaiman; Rusu, Mirabela; Sonn, Geoffrey; Estienne, Théo; Vakalopoulou, Maria; Han, Luyi; Huang, Yunzhi; Yap, Pew-Thian; Brudfors, Mikael; Balbastre, Yaël; Joutard, Samuel; Modat, Marc; Lifshitz, Gal; Raviv, Dan; Lv, Jinxin; Li, Quang; Jaouen, Vincent; Visvikis, Dimitris; Fourcade, Constance; Rubeaux, Mathieu; Pan, Wentao; Xu, Zhe; Jian, Bailiang; De Benetti, Francesca; Wodzinski, Marek; Gunnarsson, Niklas; Sjölund, Jens; Grzech, Daniel; Qiu, Huaqi; Li, Zeju; Thorley, Alexander; Duan, Jinming; Grossbröhmer, Christoph; Hoopes, Andrew; Reinertsen, Ingerid; Xiao, Yiming; Landman, Bennett; Huo, Yuankai; Murphy, Keelin; Lessmann, Nikolas; van Ginneken, Bram; Dalca, Adrian V.; Heinrich, Mattias P. (Peer reviewed; Journal article, 2022)
      Image registration is a fundamental medical image analysis task, and a wide variety of approaches have been proposed. However, only a few studies have comprehensively compared medical image registration approaches on a ...