Module Type & Category
Category: Base or (Filtering, Registration, etc.)
Authors, Collaborators & Contact
- Author1: Raúl San José Estépar, BWH
- Contributor1: Alex Yarmakovich, Isomics
- Contact: http://lmi.bwh.harvard.edu/~rjosest/address.html]
ROI Seeding is a tractography implementation that allows a user to seed tracts from a region of interest (ROI). The ROI is defined as a labelmap and has to be provided by the user. One approach to generate the ROI is by means of the Editor module.
Examples, Use Cases & Tutorials
- We want to study the white matter integrate across a population for a given tract. ROISeeding can be used to carry this study.
- First, a region of interest in the tract that is under study has to be defined for each subject, for example by manually delineating the ROI using the Editor module. The Fractional Anisotropy (FA) Volume can be used as reference volume to trace the ROI. The FA volume can be computed using Diffusion Tensor Scalar Measurements.
- Second, if the DTI volume is not direcly available, the DWI has to be loaded and the tensor has to be created using the | Diffusion Tensor Estimation.
- Third, set up the ROI Seeding using the DTI volume and the ROI labelmap as main volume inputs.
- Fourth, choose the tractography parameters. The stopping criteria are the more important parameters. Depending on the setting different results can be obtained, for example, fiber can be longer or shorter.
Quick Tour of Features and Use
The module is very straighforward to use:
- Input DTI volume:set the DTI volume that is going to be used for tractography
- Parameters panel:
- Output panel:
- Viewing panel:
Caveats and other limitations
ROISeeding module does not work when the labelmap dimensions do not match the DTI volume dimensions. The work-around is to resample labelmap using | Filtering -> Resample Volume 2.
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Source code & documentation
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