Difference between revisions of "Documentation/Nightly/Extensions/ImageCompare"

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Tag: 2017 source edit
Tag: 2017 source edit
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This extension is for comparing images.
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For the moment it contains just a single module for syntethic CT evaluation.
  
 
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{{documentation/{{documentation/version}}/module-section|Module Description}}
 
{{documentation/{{documentation/version}}/module-section|Module Description}}
 
This extension is for comparing images.
 
For the moment it contains just a single module for syntethic CT evaluation.
 
  
 
* SyntheticCTEvaluation: This module allows to quantify the similarity between a syntethic CT and a ground truth.
 
* SyntheticCTEvaluation: This module allows to quantify the similarity between a syntethic CT and a ground truth.

Revision as of 10:51, 24 January 2020

Home < Documentation < Nightly < Extensions < ImageCompare


For the latest Slicer documentation, visit the read-the-docs.


Introduction and Acknowledgements

Extension: SyntheticCTEvaluation
Author: Paolo Zaffino ()
Contributor1: Maria Francesca Spadea ()
Contact: Paolo Zaffino, <email>p.zaffino@unicz.it</email>

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 module

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

Module UI

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