2020
DOI: 10.48550/arxiv.2011.14229
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Deep Learning for Regularization Prediction in Diffeomorphic Image Registration

Abstract: This paper presents a predictive model for estimating regularization parameters of diffeomorphic image registration. We introduce a novel framework that automatically determines the parameters controlling the smoothness of diffeomorphic transformations. Our method significantly reduces the effort of parameter tuning, which is time and labor-consuming. To achieve the goal, we develop a predictive model based on deep convolutional neural networks (CNN) that learns the mapping between pairwise images and the regu… Show more

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