Image super resolution reconstruction (ISRR) is a technique that may be useful for generating fast, motion tolerant 3D reconstructed images from multi stack data. We provide initial results of a multi-step ISRR approach using patch-to-volume reconstruction(PVR) followed by a slice-by-slice convolutional neural network to further improve spatial resolution. Our methods provide improved measures of peak-SNR, and could be used to rapidly generate 3D volumes from multiple 2D stacks in fetal and abdominal imaging where constant motion requires short scan times as well as in pelvic imaging where high SNR requirements lead to long scan times and motion artifact. Motion artifact is a significant obstacle in these MRI applications resulting in image quality degradation and potentially limited diagnostic ability.
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