Difference between revisions of "DBP3:Utah:SlicerModuleAutomatedLASegmentation"
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| − | === | + | ===CMR Toolkit LA Segmentation Using Graph Cuts=== |
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Type: CLI | Type: CLI | ||
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===Quick Tour of Features and Use=== | ===Quick Tour of Features and Use=== | ||
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* Input Image : Select the cardiac LGE-MRI image volume | * Input Image : Select the cardiac LGE-MRI image volume | ||
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===Source Code & Documentation=== | ===Source Code & Documentation=== | ||
| − | + | The source code for this module can be found at the [https://github.com/carma-center/carma_slicer_extension/ CARMA GitHub repository]. | |
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Latest revision as of 19:56, 29 July 2013
Home < DBP3:Utah:SlicerModuleAutomatedLASegmentationCMR Toolkit LA Segmentation Using Graph Cuts
Authors, Collaborators & Contact
- CARMA Center, University of Utah: Gopal Veni, Salma Bengali, Alan Morris, Josh Cates, Rob MacLeod, Ross Whitaker
General Information
Module Type & Category
Type: CLI
Category: Cardiac MRI Toolkit
Module Description
This module automatically segments the left atrium from a cardiac LGE-MRI image volume. The input to the module is a cardiac LGE-MRI image, a smoothness parameter and model data. The model is arbitrarily selected and can be changed to check if it improves the segmentation output.
Usage
Examples, Use Cases & Tutorials
- This module is meant to be used for segmenting the left atrium from cardiac LGE-MRI images.
Quick Tour of Features and Use
The following are the inputs and outputs:
- Input Image : Select the cardiac LGE-MRI image volume
- Smoothness Parameter : Select the smoothness parameter value
- Model Number: Select the model number
- Output Endo Label Image: Create the output endo label image
- Output Epi Label Image: Create the output epi label image
- Model Data Directory: Select the directory of the input model
- Epi Mesh: Create the output epi mesh
- Endo Mesh: Create the output endo mesh
- Center of Left Atrium: Select the approximate center of the left atrium by placing a fiducial
Development
Source Code & Documentation
The source code for this module can be found at the CARMA GitHub repository.
