147075 20260316125347.0 doi 10.1109/ISBI56570.2024.10635118 sideral 140849 ART-2024-140849 eng Ramón-Júlvez, Ubaldo Universidad de Zaragoza EPDiff-JF-Net: Adjoint Jacobi Fields for Diffeomorphic Registration Networks 2024 Large Deformation Diffeomorphic Metric Mapping (LDDMM) is a well-established diffeomorphic registration method, a critical step for many medical imaging applications. Of special interest are its geodesic shooting variants, which enable statistical shape analysis from transformations usable in computational anatomy studies. This paper introduces a novel deep learning-based unsupervised approach for diffeomorphic image registration called EPDiff-JF-Net. Our method predicts an initial velocity field, performs geodesic shooting to obtain the corresponding path of diffeomorphisms, and utilizes an adjoint Jacobi fields layer to calculate the relevant gradients for training from parallel transport along the geodesic. The model is trained in a fully unsupervised end-to-end manner, with no requirement of ground-truth in the training loss. Experimental results on 3D brain MRI datasets demonstrate the effectiveness of EPDiff-JF-Net, outperforming EPDiff-based LDDMM and deep learning methods while significantly reducing computation time. info:eu-repo/grantAgreement/ES/DGA/T64-20R info:eu-repo/grantAgreement/ES/MICINN/PID2019-104358RB-I00 info:eu-repo/grantAgreement/ES/MICINN/PID2022-138703OB-I00 info:eu-repo/semantics/closedAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 2.5 2024 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Hernández, Mónica Universidad de Zaragoza (orcid)0000-0003-1270-5852 Mayordomo, Elvira Universidad de Zaragoza (orcid)0000-0002-9109-5337 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 2024 (2024), 1-5 Proc. (IEEE Int. Symp. Biomed. Imaging) Proceedings - International Symposium on Biomedical Imaging 1945-7928 2168389 http://zaguan.unizar.es/record/147075/files/texto_completo.pdf Versión publicada 3063034 http://zaguan.unizar.es/record/147075/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:147075 articulos driver 2026-03-16-08:29:36 ARTICLE