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Fiber bundle imaging resolution enhancement using deep learning
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DOI：10.1364/OE.27.015880.png)
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Abstract
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We propose a deep learning based method to estimate high-resolution images from multiple fiber bundle images. Our approach first aligns raw fiber bundle image sequences with a motion estimation neural network and then applies a 3D convolution neural network to learn a mapping from aligned fiber bundle image sequences to their ground truth images. Evaluations on lens tissue samples and a 1951 USAF resolution target suggest that our proposed method can significantly improve spatial resolution for fiber bundle imaging systems. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
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