Difference between revisions of "Documentation/Nightly/Extensions/DensityLungSegmentation"
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− | * | + | * Lung CT GMM Segmentation: This module, given a chest CT, labels lung tissue by fitting the intensities with a Gaussian Mixture Model already available. It can be used for pneumonia (COVID-19 too). |
Revision as of 14:36, 11 September 2021
Home < Documentation < Nightly < Extensions < DensityLungSegmentation
For the latest Slicer documentation, visit the read-the-docs. |
Introduction and Acknowledgements
Extension: DensityLungSegmentation |
This extension is for labeling lung tissue CT according to intensity.
Module Description
- Lung CT GMM Segmentation: This module, given a chest CT, labels lung tissue by fitting the intensities with a Gaussian Mixture Model already available. It can be used for pneumonia (COVID-19 too).
Use Cases
- Lung CT GMM Segmentation
User wants to segment lung tissue according to intensity (healthy, ground-glass opacities, and consolidation).
Tutorials
- Lung CT GMM Segmentation
1. Load chest CT (COVID-19 CTs can be download from https://www.imagenglab.com/newsite/covid-19/ ) 2. Select/create a labelmap for the result 3. Select/create a labelmap for the averaged result 4. Click Apply button
Panels and their use
Similar Modules
References
- Zaffino, Paolo, et al. "An Open-Source COVID-19 CT Dataset with Automatic Lung Tissue Classification for Radiomics." Bioengineering 8.2 (2021): 26. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7919807/
Information for Developers
https://github.com/pzaffino/SlicerDensityLungSegmentation
Section under construction. |