Difference between revisions of "Documentation/Nightly/Extensions/DensityLungSegmentation"
From Slicer Wiki
Tag: 2017 source edit |
Tag: 2017 source edit |
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| − | Extension: [[Documentation/{{documentation/version}}/Extensions/ | + | Extension: [[Documentation/{{documentation/version}}/Extensions/DensityLungSegmentation|DensityLungSegmentation]]<br> |
Author: Paolo Zaffino, Magna Graecia Univeristy of Catanzaro - Italy<br> | Author: Paolo Zaffino, Magna Graecia Univeristy of Catanzaro - Italy<br> | ||
Contributor1: Maria Francesca Spadea, Magna Graecia Univeristy of Catanzaro - Italy<br> | Contributor1: Maria Francesca Spadea, Magna Graecia Univeristy of Catanzaro - Italy<br> | ||
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| − | This extension is for | + | This extension is for segmentin lung tissue CT according to intensity. |
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{{documentation/{{documentation/version}}/module-section|Module Description}} | {{documentation/{{documentation/version}}/module-section|Module Description}} | ||
| − | + | This module, given a chest CT, segment lung tissue by fitting the intensities with a Gaussian Mixture Model already created. It can be used for pneumonia (COVID-19 too). | |
<!-- ---------------------------- -->{{documentation/{{documentation/version}}/module-section|Use Cases}} | <!-- ---------------------------- -->{{documentation/{{documentation/version}}/module-section|Use Cases}} | ||
| − | * Lung | + | * Lung CT GMM Segmentation |
| − | User wants to | + | User wants to segment lung tissue according to intensity (healthy, ground-glass opacities, and consolidation). |
{| | {| | ||
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{{documentation/{{documentation/version}}/module-section|Tutorials}} | {{documentation/{{documentation/version}}/module-section|Tutorials}} | ||
| − | * Lung | + | * Lung CT GMM Segmentation |
| − | 1. Load chest CT | + | |
| − | 2. Select/create a | + | 1. Load chest CT (COVID-19 CTs can be download from https://www.imagenglab.com/newsite/covid-19/ ) |
| − | 3. Select/create a | + | 2. Select/create a segmentation for the result |
| + | 3. Select/create a segmentation for the averaged result | ||
4. Click Apply button | 4. Click Apply button | ||
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{{documentation/{{documentation/version}}/module-section|References}} | {{documentation/{{documentation/version}}/module-section|References}} | ||
| − | * Zaffino, Paolo, et al. "An Open-Source COVID-19 CT Dataset with Automatic Lung Tissue Classification for Radiomics." Bioengineering 8.2 (2021): 26. | + | * 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/ |
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{{documentation/{{documentation/version}}/module-section|Information for Developers}} | {{documentation/{{documentation/version}}/module-section|Information for Developers}} | ||
| − | https://github.com/pzaffino/ | + | https://github.com/pzaffino/SlicerDensityLungSegmentation |
{{documentation/{{documentation/version}}/module-developerinfo}} | {{documentation/{{documentation/version}}/module-developerinfo}} | ||
Latest revision as of 13:14, 14 September 2021
Home < Documentation < Nightly < Extensions < DensityLungSegmentation
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For the latest Slicer documentation, visit the read-the-docs. |
Introduction and Acknowledgements
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Extension: DensityLungSegmentation |
This extension is for segmentin lung tissue CT according to intensity.
Module Description
This module, given a chest CT, segment lung tissue by fitting the intensities with a Gaussian Mixture Model already created. 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 segmentation for the result 3. Select/create a segmentation 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
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Section under construction. |
