Difference between revisions of "Projects:LMMSERicianDWINoiseRemoval"
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''Example results'' | ''Example results'' | ||
− | [[Image:Glyph_orig_rician_LMMSE.png | + | [[Image:Glyph_orig_rician_LMMSE.png|thumb|300px|FA values and direction of major tensor eigenvalue based on original DWI data.]] |
− | [[Image:Glyph_f10_rician_LMMSE.png | + | [[Image:Glyph_f10_rician_LMMSE.png|thumb|300px|FA values and direction of major tensor eigenvalue after filtering the DWI data using the LMMSE filter.]] |
''References'' | ''References'' |
Revision as of 14:07, 4 September 2007
Home < Projects:LMMSERicianDWINoiseRemovalRestoration of DWI data using a Rician LMMSE Estimator
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Objectives
Provide a way for noise removal in diffusion weighted images incorporating the Rician noise model. The Rician noise level is estimated automatically and used to parametrize the local Linear Minimum Mean Squared Error estimator.
Progress
The method was evaluated on real and synthetic datasets. A Slicer 3 module was developed.
Example results
References
- Aja-Fernandez, S., Alberola-Lopez, C., Westin, C.F., "Filtering and noise estimation in magnitude MRI and Rician distributed images," submitted to IEEE Transactions on Image Processing.
- Aja-Fernandez, S., Niethammer, M., Kubicki, M., Shenton, M.E., Westin, C.-F., "Restoration of DWI data using a Rician LMMSE estimator," submitted to MRM.
Key Investigators
- BWH: Santiago Aja-Fernandez, Marc Niethammer, Marek Kubicki, Martha Shenton, Carl-Fredrik Westin
Links