Since the development of deep learning methods, many researchers have focused on image quality improvement using convolutional neural networks. They proved its effectivity in noise reduction, single-image super-resolution, and segmentation. In this study, we apply stacked U-Net, a deep learning method, for X-ray computed tomography image reconstruction to generate high-quality images in a short time with a small number of projections.
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