LDDMM Meets GANs: Generative Adversarial Networks for Diffeomorphic Registration
Resumen
In this work, we propose an unsupervised adversarial learning LDDMM method for 3D mono-modal images based on Generative Adversarial Networks. We have successfully implemented two models with stationary and EPDiff constrained non-stationary parameterizations of diffeomorphisms. Our approach has shown a competitive performance with respect to benchmark supervised and model-based methods.
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Publicado
2021-11-12
Número
Sección
Artículos (Tecnologías de la Información y las Comunicaciones)