Tomographic data for testing, demonstrating, and developing methods of removing ring artifacts
<p>These tomographic data were used for demonstrating our methods of eliminating ring artifacts published in Optics Express, <em>Nghia T. Vo, Robert C. Atwood, and Michael Drakopoulos, "Superior techniques for eliminating ring artifacts in X-ray micro-tomography," <strong>26</strong>, 28396-28412 (2018)</em><em>. </em>In sinogram, the artifacts appear as straight lines or stripe artifacts. The data have many types of stripe artifacts: full stripes, partial stripes, unresponsive stripes, fluctuating stripes, and blurry stripes. They are very useful for testing and developing methods of removing ring artifacts.</p> <p>Documentation: <a href="https://sarepy.readthedocs.io/">https://sarepy.readthedocs.io/</a></p> <p>Python implementations of these methods:</p> <p><a href="https://github.com/nghia-vo/sarepy">https://github.com/nghia-vo/sarepy</a></p> <p>In Tomopy:</p> <p><a href="https://tomopy.readthedocs.io/en/latest/api/tomopy.prep.stripe.html">https://tomopy.readthedocs.io/en/latest/api/tomopy.prep.stripe.html</a></p> <p>In Savu:</p> <p><a href="http://github.com/DiamondLightSource/Savu/tree/master/savu/plugins/ring_removal">https://github.com/DiamondLightSource/Savu/tree/master/savu/plugins/ring_removal</a></p> <p>In Algotom:</p> <p><a href="https://github.com/algotom/algotom/blob/master/algotom/prep/removal.py">https://github.com/algotom/algotom/blob/master/algotom/prep/removal.py</a> </p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0