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 unsupervisedapproach for diffeomorphic image registrationcalled EPDiff-JF-Net. We propose a novel paralleltransport layer to compute the gradients necessaryfor training with adjoint Jacobi fields. We test ourmethod on two independent brain MRI datasets andobtain state-of-the-art results.