Difference between revisions of "Projects:LMMSERicianDWINoiseRemoval"
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| + | = Restoration of DWI data using a Rician LMMSE Estimator = | ||
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| + | [[Image:Glyph_orig_rician_LMMSE.png|thumb|300px|FA values and direction of major tensor eigenvalue based on original DWI data.]] | ||
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| + | [[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.]] | ||
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| + | Our Objective is to 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. | Linear Minimum Mean Squared Error estimator. | ||
| − | + | = Description = | |
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| + | The method was evaluated on real and synthetic datasets. A Slicer 3 module was developed. | ||
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| + | = Publications = | ||
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| + | ''In Press'' | ||
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* 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., 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. | * 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 = | |
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| − | + | * BWH: Santiago Aja-Fernandez, Marc Niethammer, Marek Kubicki, Martha Shenton, Carl-Fredrik Westin | |
Latest revision as of 20:12, 27 November 2007
Home < Projects:LMMSERicianDWINoiseRemovalBack to NA-MIC_Collaborations
Contents
Restoration of DWI data using a Rician LMMSE Estimator
Our Objective is to 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.
Description
The method was evaluated on real and synthetic datasets. A Slicer 3 module was developed.
Publications
In Press
- 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
