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A reconstruction method for cardiac cine magnetic resonance images is proposed that is based on the combined use of the notion of analytic image and neural network based learning. The analytic image is used to exploit spectral or k-space information and the neural network for a better estimation of missing temporal information. The results show that the proposed approach allows a 4-factor reduction...
Previously proposed singularity function models are suitable only for representing real data. However, in a number of application domains such as magnetic resonance imaging, the initial raw data are complex images, which requires new image models for representing them. In this paper, a novel singularity function analysis model is proposed that represents a complex discrete signal or image as a linear...
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