Documentation/Nightly/Modules/FiberBundleLabelSelect

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Introduction and Acknowledgements

Title: Tractography ROI Selection Author(s)/Contributor(s): Demian Wassermann, Fan Zhang, Lauren O'Donnell (SPL, LMI, BWH, SlicerDMRI) License: 3D Slicer Contribution and Software License Agreement Acknowledgements: The SlicerDMRI developers gratefully acknowledge funding for this project provided by NIH NCI ITCR U01CA199459 (Open Source Diffusion MRI Technology For Brain Cancer Research), NIH P41EB015898 (National Center for Image-Guided Therapy) and NIH P41EB015902 (Neuroimaging Analysis Center), as well as 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. Contact: <email>slicer-users@bwh.harvard.edu</email> Website: http://slicerdmri.github.io/

SlicerDMRI   Surgical Planning Laboratory   NAC   Whole brain tractography   Corpus callosum (CC) tract selection

Module Description

Fiber bundle label select allows a user to select tracts passing or not passing through single or multiple labels. (Selection region label maps may be created with the Editor module or other segmentation tools.)

Use Cases

Most frequently used for these scenarios:

• Use Case 1: Filter out a subset of DTI fiber tracts which are passing through selected region(s) defined in the label map volume.
• Use Case 2: Filter out a subset of DTI fiber tracts which are NOT passing through selected region(s) defined in the label map volume.
• Use Case 3: A combination of Case 1 and Case 2.

Tutorials

Links to tutorials that use this module

• Slicer4 Fiber Bundle Selection and Scalar Measurements Tutorial: https://www.slicer.org/slicerWiki/index.php/Documentation/4.5/Training#Fiber_Bundle_Selection_and_Scalar_Measurements

Panels and their use

Parameters:

• IO: Input/output parameters
  • Selection Region Label Map (InputLabel_A): Label map volume defining selection region
  • Input Fiber Bundle (InputFibers): Input tractography for region-based selection.
  • Output Fiber Bundle (OutputFibers): Selected tractography result from region-based selection.
• Tract selection region labels:
  • Inclusion labels (comma-separated) (PassLabel): Comma-separated list of label values defining inclusion region. Fibers passing through these labels will be retained.
  • Inclusion label combination logic (PassOperation): AND: Fiber must pass through all specified labels.
    OR: Fiber must pass through any specified label (at least one).
  • Exclusion labels (comma-separated) (NotPassLabel): Comma-separated list of label values defining exclusion region. Fibers passing through these labels will be removed.
  • Exclusion label combination logic (NoPassOperation): AND: Any fiber passing through all specified labels is excluded.
    OR: Fibers passing through any specified label (at least one) are excluded.
• Advanced Settings: Advanced settings
  • Sampling distance (mm) (SamplingDistance): Sampling Distance

List of parameters generated transforming this XML file using this XSL file. To update the URL of the XML file, edit this page.

REMOVE THIS FROM BELOW WHEN AUTO GENERATED: A list of all the panels in the interface, their features, what they mean, and how to use them. For instance:

Parameters panel: Parameters: select an existing setting for the module or create a new one. IO panel: Input Label Map: select an existing label map volume. Input FiberBundle: Select the fibers that you want to filter. Output FiberBundle: Select the bundle that you want to create or modify from a list. Label Regions Definition panel : Labels to include: A comma separated list of label values to include in the output fiber bundles set. Combine Include Labels: OR or AND logical operation to combine individual label values in the above list. Labels to exclude: A comma separated list of label values to exclude from the output fiber bundles set. Combine Exclude Labels: OR or AND logical operation to combine individual label values in the above list. Similar Modules Tractography Label Map Seeding References http://slicerdmri.github.io/ Information for Developers https://github.com/SlicerDMRI