EPDIFF-JF-NET: Adjoint Jacobi Fields for Diffeomorphic Registration Networks
Ubaldo Ramon-Julvez, Mónica Hernández Giménez, Elvira Mayordomo Cámara · Jornadas 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.