High-resolution brain fMRI reconstruction via double cooperative network learning

For the problem of resolution enhancement of function Magnetic Resonance Imaging(fMRI), traditional methods based on prior knowledge are difficult to choose appropriate regularization terms to solve it effectively. In this work, we proposed a double cooperative network without regularization items for super-resolution(SR) reconstruction. The experimental results show that the proposed method could effectively enhance the resolution of functional magnetic resonance images and rebuild fine texture. Also we demonstrate the proposed method is robustness on various tasks fMRI.

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