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, Magna Graecia Univeristy of Catanzaro - Italy<br> | |
| − | + | Contributor1: Maria Francesca Spadea, Magna Graecia Univeristy of Catanzaro - Italy<br> | |
| − | + | Contact: Paolo Zaffino, <email>p.zaffino@unicz.it</email><br> | |
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{{documentation/{{documentation/version}}/module-introduction-end}} | {{documentation/{{documentation/version}}/module-introduction-end}} | ||
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| + | This extension is for comparing images. | ||
| + | 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}} | ||
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| + | * SyntheticCTEvaluation: This module allows to quantify the similarity between a syntethic CT and a ground truth. | ||
| + | <!-- ---------------------------- -->{{documentation/{{documentation/version}}/module-section|Use Cases}} | ||
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| + | * Synthetic CT Evaluation | ||
| + | User wants to quantify conversion accuracy of his algorithm for synthetic CT generation | ||
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| − | |[[Image: | + | |[[Image:SlicerSyntheticCTEvaluation_screenshot.png|thumb|340px|Synthetic CT Evaluation module]] |
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{{documentation/{{documentation/version}}/module-section|Tutorials}} | {{documentation/{{documentation/version}}/module-section|Tutorials}} | ||
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| + | * 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 | ||
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| − | |[[Image: | + | |[[Image:SlicerSyntheticCTEvaluation_panel.png|thumb|280px|Synthetic CT Evaluation module UI]] |
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| − | * | + | *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. |
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{{documentation/{{documentation/version}}/module-section|Information for Developers}} | {{documentation/{{documentation/version}}/module-section|Information for Developers}} | ||
| + | https://github.com/pzaffino/SlicerImageCompare | ||
{{documentation/{{documentation/version}}/module-developerinfo}} | {{documentation/{{documentation/version}}/module-developerinfo}} | ||
Latest revision as of 10:59, 24 January 2020
Home < Documentation < Nightly < Extensions < ImageCompare
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For the latest Slicer documentation, visit the read-the-docs. |
Introduction and Acknowledgements
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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
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Section under construction. |
