Modules:MaskImage-Documentation-3.6
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Mask Image
Mask Image
General Information
Module Type & Category
Type: CLI
Category: Filtering, Arithmetic
Authors, Collaborators & Contact
- Nicole Aucoin, Brigham and Women's Hospital
- Contact: Nicole Aucoin, nicole@bwh.harvard.edu
Module Description
Apply a labelmap as a mask and set all pixels outside the mask (i.e. not matching the label value) to zero (or a given replacement value)
Usage
Use Cases, Examples
This module is especially appropriate for these use cases:
- Use Case 1: masking unwanted structures in processes that do not support masking directly.
Examples of the module in use:
- Example 1:
Tutorials
Links to tutorials explaining how to use this module:
Quick Tour of Features and Use
- Input and Output:
- Input Volume: the image to be masked
- Mask Volume: labelmap containing the region to be preserved as a specific (single) label value
- Masked Volume: result image created. Equals the Input Volume with all voxels not part of the mask replaced.
- Settings:
- Label Value: value of the Mask Volume to use as ROI. All voxels not matching this value will be replaced. All voxels matching this value will be preserved.
- Replace Value: value to set for all voxels "outside" the mask. To remove unwanted structure, zero (0) is the common default. All voxels not matching the Label Value above will be set to this Replace Value.
Development
Notes from the Developer(s)
This is a wrapper around the itk::ThresholdImageFilter.
Dependencies
The Volumes module is required for this module's use.
Tests
On the Dashboard, these tests verify that the module is working on various platforms:
Known bugs
Follow this link to the Slicer3 bug tracker.
Usability issues
Follow this link to the Slicer3 bug tracker. Please select the usability issue category when browsing or contributing.
Source code & documentation
More Information
Acknowledgment
This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149.
