Documentation/4.0/Modules/MRIBiasFieldCorrection
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Introduction and Acknowledgements
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This work is part of the National Alliance for Medical Image Computing (NA-MIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Information on NA-MIC can be obtained from the NA-MIC website. | |||||
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Module Description
Corrects 3D MRI images corrupted by MRI gain field effect. This module removes the slow-varying intensity variation from a 3D image. The output image has a higher contrast locally and the visualization and reading of the image are improved. This is an important pre-processinbg step for image operations requiring intensity perfect images, such as the Expectation Maximization segmentation (see EMSegment module). The N3 and N4 methods are described in N4ITK: Nick's N3 ITK Implementation For MRI Bias Field Correction, Tustison N., Gee J., Insight Journal, 2009. http://hdl.handle.net/10380/3053 The Slicer code was contributed by Sylvain Jaume (MIT) for NA-MIC (http://na-mic.org).
Use Cases
Most frequently used for these scenarios:
- Use Case 1:
Tutorials
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Panels
Parameters:
- IO
- Input Image: Input image
- Input Mask: Input mask
- Output Image: Corrected image
- Parameters for the algorithm
- Algorithm type: Select your algorithm
- Shrink factor: Shrink the image by this factor
- Maximum number of iterations: Number of iterations
- Number of fitting levels: Set the number of fitting levels
- Wiener filter noise: Set the Wiener filter noise
- Bias full width at half maximum: Set the bias field full width at half maximum
- Convergence threshold: Set the convergence threshold
Similar Modules
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References
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Information for Developers
| Section under construction. |
