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Denoising medical images by learning sparse image representations with a deep unfolding approach
Denoising medical images by learning sparse image representations with a deep unfolding approach
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机译:通过使用深度展开方法学习稀疏图像表示来对医学图像进行降噪
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摘要
The present embodiments relate to denoising medical images. By way of introduction, the present embodiments described below include apparatuses and methods for machine learning sparse image representations with deep unfolding and deploying the machine learnt network to denoise medical images. Iterative thresholding is performed using a deep neural network by training each layer of the network as an iteration of an iterative shrinkage algorithm. The deep neural network is randomly initialized and trained independently with a patch-based approach to learn sparse image representations for denoising image data. The different layers of the deep neural network are unfolded into a feed-forward network trained end-to-end.
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