Original paper
Super-resolution magnetic resonance imaging reconstruction using deep attention networks
Published: Mar 10, 2020
Abstract
We propose a deep-learning-based method to reconstruct super-resolution images from routinely captured MRI images. We propose to integrate a deeply supervised attention model into a generative adversarial network (GAN)-based framework to improve MRI image resolution. Deep attention GANs are introduced to enable end-to-end encoding-and-decoding learning. Next, an attention model is used to retrieve the most relevant information from the encoder....
Paper Details
Title
Super-resolution magnetic resonance imaging reconstruction using deep attention networks
Published Date
Mar 10, 2020
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