Documentation/Nightly/Extensions/SlicerDMRI

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Introduction and Acknowledgements

Extension: SlicerDMRI Acknowledgments: This work is supported in part by the National Cancer Institute and the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health through the following grants: NIH NCI ITCR U01CA199459 (Open Source Diffusion MRI Technology For Brain Cancer Research) NIH P41EB015898 (National Center for Image-Guided Therapy) NIH P41EB015902 (Neuroimaging Analysis Center) 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. Major Contributors: Lauren J. O'Donnell (SPL), Isaiah Norton (Brigham and Women's Hospital), Raul San Jose Estepar (Brigham and Women's Hospital), Carl-Fredrik Westin (Brigham and Women's Hospital), Alex Yarmarkovich License: Slicer License

SlicerDMRI   Surgical Planning Laboratory   NAC   NCIGT

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Extension Description

SlicerDMRI extension hosts various modules to facilitate

• processing and management of diffusion MRI image data
• utilizing diffusion MRI tractography for neuroscience studies and for planning image-guided interventions
• quantitative analysis of diffusion MRI data

Modules

• DICOM2Full Brain Tractography:
• Diffusion Brain Masking: Creates a brain mask from a diffusion weighted image volume
• Diffusion Tensor Estimation: Estimates the diffusion tensor model from diffusion weighted images.
• Diffusion Tensor Scalar Maps: Computes scalar measures from a diffusion tensor dataset.
• DWIConverter: Converts diffusion weighted MR images in dicom series into Nrrd format for analysis in Slicer.
• DWI to Full Brain Tractography:
• Resample DTIVolume: Implements DT image resampling through the use of itk Transforms.
• Resample Scalar/Vector/DWI Volume: Implements image and vector-image resampling through the use of its Transforms.
• Tractography Display: Allows the user to modify the display of diffusion tractography.
• Tractography Measurements: Computes whole-fiber scalar measurements from a directory of VTK fiber bundle files
• Tractography ROI Selection: Allows a user to select tracts passing or not passing through single or multiple labels.
• Tractography ROI Seeding: Seeds tractography from a Diffusion Tensor Image (DTI) within a region defined by a label map.
• Tractography Seeding: Allows interactive seeding of DTI fiber tracts starting from a list of fiducial points or vertices of a model, or a label map volume.
• Tractography to Mask Image: Allows a user to set the specified label value in the label map at every vertex in each of the fibers in a bundle.
• UKFTractography: Traces fibers in a DWI Volume using the multiple tensor unscented Kalman Filter methodology.

References

[1] O’Donnell LJ, Westin CF. An introduction to diffusion tensor image analysis. Neurosurgery clinics of North America. 2011 Apr 30;22(2):185-96.

Information for Developers

• SlicerSlicerDMRI organization page on github: https://github.com/SlicerDMRI