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Fast Improvement of TEM Images with Low-Dose Electrons by Deep Learning
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Title: | Fast Improvement of TEM Images with Low-Dose Electrons by Deep Learning |
Authors: | Katsuno, Hiroyasu Browse this author →KAKEN DB | Kimura, Yuki Browse this author →KAKEN DB | Yamazaki, Tomoya Browse this author | Takigawa, Ichigaku Browse this author →KAKEN DB |
Keywords: | deep learning | fast improvement | nanoparticles | transmission electron microscopy |
Issue Date: | 10-Dec-2021 |
Publisher: | Cambridge University Press |
Journal Title: | Microscopy and microanalysis |
Volume: | 28 |
Issue: | 1 |
Start Page: | 138 |
End Page: | 144 |
Publisher DOI: | 10.1017/S1431927621013799 |
Abstract: | Low electron dose observation is indispensable for observing various samples using a transmission electron microscope; consequently, image processing has been used to improve transmission electron microscopy (TEM) images. To apply such image processing to in situ observations, we here apply a convolutional neural network to TEM imaging. Using a dataset that includes short-exposure images and long-exposure images, we develop a pipeline for processed short-exposure images, based on end-to-end training. The quality of images acquired with a total dose of approximately 5 e(-) per pixel becomes comparable to that of images acquired with a total dose of approximately 1,000 e(-) per pixel. Because the conversion time is approximately 8 ms, in situ observation at 125 fps is possible. This imaging technique enables in situ observation of electron-beam-sensitive specimens. |
Rights: | This article has been published in a revised form in Microscopy and microanalysis https://doi.org/10.1017/S1431927621013799. This version is published under a Creative Commons CC-BY-NC-ND. No commercial re-distribution or re-use allowed. Derivative works cannot be distributed. ©The Author(s), 2021. | https://creativecommons.org/licenses/by-nc-nd/4.0/ |
Type: | article (author version) |
URI: | http://hdl.handle.net/2115/85768 |
Appears in Collections: | 低温科学研究所 (Institute of Low Temperature Science) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 勝野 弘康
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