Explainability of deep neural networks is one of the most challenging and interesting problems in the field . We show that such an approach can decompose the highly convoluted latent latent spaces of registration pipelines in an orthogonal space with several interesting properties . We hope that this work could shed some light on a better understanding of deep learning-basedregistration methods. We perform experiments using two different . differentdatasets focusing on lungs and hippocampus MRI MRI. We hope this workcould shed some . light on the . better . understanding of the deep learning . methods .

Author(s) : Théo Estienne, Maria Vakalopoulou, Stergios Christodoulidis, Enzo Battistella, Théophraste Henry, Marvin Lerousseau, Amaury Leroy, Guillaume Chassagnon, Marie-Pierre Revel, Nikos Paragios, Eric Deutsch

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Keywords : deep - latent - shed - methods - light -

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