Data for Unsupervised Sinogram Inpainting for Nanoparticle Electron Tomography (UsiNet) for missing wedge correction
Citation:
Yao, Lehan; Lyu, Zhiheng; Li, Jiahui; Chen, Qian (2023): Data for Unsupervised Sinogram Inpainting for Nanoparticle Electron Tomography (UsiNet) for missing wedge correction. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7963044_V1
Persistent link for this dataset:
Dataset Description

Example data for https://github.com/chenlabUIUC/UsiNet
The data contains computer simulated and experimental tilting series (or sinograms) of gold nanoparticles.
Two training data examples are provided:
1. simulated_data.zip
2. experimental_data.zip
In each zip folder, we include an image_data.zip and a training_data.zip. The former is for viewing and only the latter is needed for model training. For more details, please refer to our GitHub repository.
Subject Physical Sciences
Keywords electron tomography; deep learning
License CC BY
Corresponding Creator Qian Chen
Downloaded 29 times
Version DOI Comment Publication Date
1 10.13012/B2IDB-7963044_V1 2023-04-06
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update: {"version_comment"=>[nil, ""], "subject"=>[nil, "Physical Sciences"]} 2023-05-11T18:22:36Z