EPDIFF-JF-NET: Adjoint Jacobi Fields for Diffeomorphic Registration Networks - Ramon Julvez, Ubaldo; Hernández Giménez, Mónica; Mayordomo Cámara, Elvira (Jornada de Jóvenes Investigadores del I3A, 2024)
This paper presents a deep learning unsupervised approach for diffeomorphic image registration called EPDiff-JF-Net. We propose a novel parallel transport layer to compute the gradients necessary for training with adjoint Jacobi fields. We test our method on two independent brain MRI datasets and obtain state-of-the-art results.