
The author presents GDCNet, a novel approach for distortion correction in fMRI using deep learning, specifically focusing on the estimation of a geometric distortion map from T1-weighted anatomical images. The core argument revolves around the efficiency and accuracy of GDCNet compared to traditional methods.


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GDCNet-Calibrationless-Geometric-Distortion-Correction-of-Echo-Planar-Imaging-Data-Using-Deep-Learning


GDCNet: Calibrationless Geometric Distortion Correction of Echo Planar Imaging Data Using Deep Learning


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GDCNet demonstrates fast distortion correction of functional images using deep learning, outperforming traditional methods.
