The authors propose a new model using a convolutional neural network (CNN) named k-t CNN for approximating non-linear spatio-temporal mappings used in various applications. Existing studies imply that spatio-temporal mappings are non-linear. Most existing studies developed various methods using linear models for spatio-temporal applications. Meanwhile, the effectiveness of non-linear models was shown for spatial-domain applications.
As an application of k-t CNN, the effectiveness of the proposed method is shown experimentally in the case of reconstruction of stack-of-spirals k-space data.
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