Variable Fraunhofer MEVIS RegLib Comprehensively Applied to Learn2Reg Challenge

In this paper, we present our contribution to the learn2reg challenge. We applied the Fraunhofer MEVIS registration library RegLib comprehensively to all 4 tasks of the challenge. For tasks 1â3, we used a classic iterative registration method with NGF distance measure, second order curvature regularizer, and a multi-level optimization scheme. For task 4, a deep learning approach with a weakly supervised trained U-Net was applied using the same cost function as in the iterative approach.