Documentation/Nightly/Modules/BasicBrainTissues
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Introduction and Acknowledgements
Extension: BrainTissuesExtension | |||||||
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Module Description
This module offer a simple and robust brain tissue segmentation focused on white matter, gray matter and CSF brain tissues. The method applied here is based on K-Means clustering segmentation, which presents best results with high quality T1 weighted MRI images.
NOTE: This module can be used alone (only apply the K-Means segmentation method on the input data), but the Brain Structures Segmenter module already use it internally, which control a image processing pipeline for a better brain tissue segmentation result.
Use Cases
- Use Case 1: Separate White Matter, Gray Matter and CSF brain tissues from a strucutral MRI image.
- There are some image processing strategies that may need a specific brain tissue mask and this module could facilitate this task. For instance, a Multiple Sclerosis lesion detection algorithm may need a White Matter mask in order to define a localized brain region where the lesion are more probable to appear.
Panels and their use
IO:
- Input Volume
- Input volume. The algorithm works better with high resolution T1 MRI images alread brain extract and inhomogeneity corrected
- Image Modality
- Select the image modality inserted as a input volume
- Brain Mask
- Output brain tissue mask
Tissue Type Output:
- Separate one tissue class
- Choose if you want all the tissues classes or only one class segmented
- Tissue
- Choose what is the brain tissue label that you want as the output label
Similar Modules
References
N/A
Information for Developers
Section under construction. |