Published January 29, 2021
| Version v0.1
Software
Open
Source Code and Supplementary Material for "Quantitative comparison of deep learning-based image reconstruction methods for low-dose and sparse-angle CT applications"
Creators
- 1. University of Bremen
- 2. Centrum Wiskunde & Informatica
- 3. Eindhoven University of Technology
Description
Code and supplementing material for the article "Quantitative comparison of deep learning-based image reconstruction methods for low-dose and sparse-angle CT applications"
Files
jleuschn/learned_ct_reco_comparison_paper-v0.1.zip
Files
(950.6 kB)
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md5:81cffc4335aa4127b7a3cc97a8305945
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Additional details
Related works
- Is supplement to
- https://github.com/jleuschn/learned_ct_reco_comparison_paper/tree/v0.1 (URL)