Modules:MRIBiasFieldCorrection-Documentation-3.5

Return to Slicer 3.5 Documentation

Gallery of New Features

MRI Bias Field Correction

Filtering:MRIBiasFieldCorrection

Input image suffering intensity inhomogeneity (visible vertically)

Output image after bias field correction (intensities are homogeneous from top to bottom of image)

General Information

Module Type & Category

Type: Interactive or CLI

Category: Filtering

Authors, Collaborators & Contact

• Nicolas Rannou: Harvard Medical School, Brigham and Women's Hospital
• Sylvain Jaume: MIT Computer Science and Artificial Intelligence Laboratory
• Contact: Nicolas Rannou <nrannou at bwh.harvard.edu>

Module Description

The module filters the image to remove the intensity inhomogeneity due to the MRI image acquisition.

Usage

• Load the input dataset (Add Volume)
• Go to the menu Modules > Filtering > MRI Bias Field Correction
• Select the input dataset
• Modify the number of iterations (large values make the processing longer)
• Modify the fitting levels
• Click on Apply (processing of large images take in the order of minutes)
• Select the 'field' checkbox if you want to visualize the field

Examples, Use Cases & Tutorials

• Note use cases for which this module is especially appropriate, and/or link to examples. (to be defined)
• Link to examples of the module's use (to be defined)
• Link to any existing tutorials (to be defined)

Quick Tour of Features and Use

List all the panels in your interface, their features, what they mean, and how to use them. For instance:

• Input panel:
• Parameters panel:
• Output panel:
• Viewing panel:

Development

Dependencies

Other modules or packages that are required for this module's use.

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

Customize following links for your module.

Links to documentation generated by doxygen.

More Information

Acknowledgment

Include funding and other support here.

References

• A Nonparametric Method for Automatic Correction of Intensity Nonuniformity in MRI Data, J.G. Sled, A.P. Zijdenbos, and A.C. Evans, IEEE Transactions on Medical Imaging, 17(1):87–97, Feb 1998.
• Parametric Estimate of Intensity Inhomogeneities Applied to MRI, M. Styner, C. Brechbhler, G. Szekely, and G. Gerig, IEEE Transactions on Medical Imaging, 19(3):153–165, Mar 2000.
• N4ITK: Nick's N3 ITK Implementation For MRI Bias Field Correction, Tustison N., Gee J., Insight Journal, 2009.