supported by The Human Brain Project
Search results
- Name
- diffusion_smoothing_tool
- Byline
- Draper Lab & MGH
- Description
- This tool implements a unified approach to variational smoothing and segmentation to brain diffusion tensor image data along user-selected attributes derived from the tensor, with the aim of extracting detailed brain structure information. The application of this framework simultaneously segments and denoises to produce edges and smoothed regions within the white matter of the brain that are relatively homogeneous with respect to the diffusion tensor attributes of choice.
- NIfTI-1 support
- Creator
- Mukund Desai & Rami Mangoubi
- Contact
- dave@cma.mgh.harvard.edu
- WWW
- http://www.cma.mgh.harvard.edu/HBP_RO1/Diffusion_Smoothing_Code/
- Availability
- Currently available at tool website.
- How to get
- Web-based download.
- Current version
- 1.0
- Current version release date
- 7/1/06
- Open source
- Yes
- License
- Available free of charge
- Yes
- Requirements
- Requires Matlab
- Technical publications
- Desai, M., D. Kennedy, Mangoubi R, Shah J, Karl C, Worth A, Makris N, Pien H. “Model-Based Variational Smoothing and Segmentation for Diffusion Tensor Imaging in the Brain”, Neuroinformatics, 4(3):217-34 2006.
- Applications publications
- Other information
- Keywords
- diffusion, smoothing
- Platforms
- MATLAB
- IATR listing last updated
- 10 Oct 2006
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