000131321 001__ 131321
000131321 005__ 20240207154753.0
000131321 0247_ $$2doi$$a10.1007/978-3-031-11203-4_3
000131321 0248_ $$2sideral$$a132140
000131321 037__ $$aART-2022-132140
000131321 041__ $$aeng
000131321 100__ $$aRamón Júlvez, Ubaldo$$uUniversidad de Zaragoza
000131321 245__ $$aLDDMM meets GANs: generative adversarial networks for diffeomorphic registration
000131321 260__ $$c2022
000131321 5203_ $$aThe purpose of this work is to contribute to the state of the art of deep-learning methods for diffeomorphic registration. We propose an adversarial learning LDDMM method for pairs of 3D mono-modal images based on Generative Adversarial Networks. The method is inspired by the recent literature on deformable image registration with adversarial learning. We combine the best performing generative, discriminative, and adversarial ingredients from the state of the art within the LDDMM paradigm. We have successfully implemented two models with the stationary and the EPDiff-constrained non-stationary parameterizations of diffeomorphisms. Our unsupervised learning approach has shown competitive performance with respect to benchmark supervised learning and model-based methods.
000131321 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000131321 592__ $$a0.32$$b2022
000131321 593__ $$aComputer Science (miscellaneous)$$c2022$$dQ3
000131321 593__ $$aTheoretical Computer Science$$c2022$$dQ4
000131321 594__ $$a2.2$$b2022
000131321 655_4 $$ainfo:eu-repo/semantics/conferenceObject$$vinfo:eu-repo/semantics/acceptedVersion
000131321 700__ $$0(orcid)0000-0003-1270-5852$$aHernández Giménez, Mónica$$uUniversidad de Zaragoza
000131321 700__ $$0(orcid)0000-0002-9109-5337$$aMayordomo Cámara, Elvira$$uUniversidad de Zaragoza
000131321 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000131321 773__ $$g13386 (2022), 18-28$$pLect. notes comput. sci.$$tLecture Notes in Computer Science$$x0302-9743
000131321 8564_ $$s3029976$$uhttps://zaguan.unizar.es/record/131321/files/texto_completo.pdf$$yPostprint
000131321 8564_ $$s1637113$$uhttps://zaguan.unizar.es/record/131321/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000131321 909CO $$ooai:zaguan.unizar.es:131321$$particulos$$pdriver
000131321 951__ $$a2024-02-07-14:40:36
000131321 980__ $$aARTICLE