Difference between revisions of "Documentation/Nightly/Extensions/ImageCompare"
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− | Extension: [[Documentation/{{documentation/version}}/Extensions/ | + | Extension: [[Documentation/{{documentation/version}}/Extensions/ImageCompare|ImageCompare]]<br> |
Author: Paolo Zaffino ({{collaborator|name|Magna Graecia Univeristy of Catanzaro - Italy}})<br> | Author: Paolo Zaffino ({{collaborator|name|Magna Graecia Univeristy of Catanzaro - Italy}})<br> | ||
Contributor1: Maria Francesca Spadea ({{collaborator|name|Magna Graecia Univeristy of Catanzaro - Italy}})<br> | Contributor1: Maria Francesca Spadea ({{collaborator|name|Magna Graecia Univeristy of Catanzaro - Italy}})<br> |
Revision as of 10:55, 24 January 2020
Home < Documentation < Nightly < Extensions < ImageCompare
For the latest Slicer documentation, visit the read-the-docs. |
Introduction and Acknowledgements
Extension: ImageCompare |
This extension is for comparing images. For the moment it contains just a single module for syntethic CT evaluation.
Module Description
- SyntheticCTEvaluation: This module allows to quantify the similarity between a syntethic CT and a ground truth.
Use Cases
- Synthetic CT Evaluation
User wants to quantify conversion accuracy of his algorithm for synthetic CT generation
Tutorials
- Synthetic CT Evaluation
1. Load ground truth CT 2. Load synthetic CT 3. Load/generate a mask of patient's outilne 4. Click Apply button
Panels and their use
Similar Modules
References
- Spadea MF, Pileggi G, Zaffino P, Salome P, Catana C, Izquierdo-Garcia D, Amato F, Seco J. Deep Convolution Neural Network (DCNN) Multiplane Approach to Synthetic CT Generation From MR images—Application in Brain Proton Therapy. International Journal of Radiation Oncology* Biology* Physics. 2019 Nov 1;105(3):495-503.
Information for Developers
https://github.com/pzaffino/SlicerImageCompare
Section under construction. |