doi:10.26754/jjii3a.202410613engRamón Júlvez, UbaldoHernández Giménez, MónicaMayordomo Cámara, ElviraEPDIFF-JF-NET: Adjoint Jacobi Fields for Diffeomorphic Registration NetworksART-2024-140850This 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.2024http://zaguan.unizar.es/record/14717110.26754/jjii3a.202410613http://zaguan.unizar.es/record/147171oai:zaguan.unizar.es:147171info:eu-repo/grantAgreement/ES/DGA/T64-20Rinfo:eu-repo/grantAgreement/ES/MICINN/PID2019-104358RB-I00info:eu-repo/grantAgreement/ES/MICINN/PID2022-138703OB-I00Jornada de jóvenes investigadores del I3A 12 (2024), [2 pp.]by-nchttp://creativecommons.org/licenses/by-nc/3.0/es/info:eu-repo/semantics/openAccess