Difference between revisions of "Projects:DTIRicianNoiseRemoval"
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+ | Back to [[NA-MIC_Collaborations|NA-MIC_Collaborations]], [[Algorithm:Utah|Utah Algorithms]] | ||
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= DTI Rician Noise Removal = | = DTI Rician Noise Removal = | ||
− | + | [[Image:DTIFiltering.jpg|thumb|512px|Coronal slice from a noisy DTI (left). The same slice after applying our Rician noise DTI filtering method (right)]] | |
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+ | Our Objective is to provide a software tool for clinicians that will filter diffusion tensor images using our Rician noise removal algorithm. The method should be completely automatic and give the user the option of reviewing the images to make sure that the results are acceptable. | ||
− | + | = Description = | |
− | + | Developed a Slicer module for our DT-MRI Rician noise removal during the [[2007_Project_Half_Week|2007 Project Half Week]]. Also enhanced the method by including an automatic method for determining the noise sigma in the image. This makes the algorithm completely automatic, i.e., there are no free parameters. Also, since the module is implemented in Slicer, images can be reviewed directly in the Slicer program after applying the filter. | |
− | + | = Publications = | |
− | + | [http://www.na-mic.org/Special:Publications?text=Projects%3ADTIRicianNoiseRemoval&submit=Search&words=all&title=checked&keywords=checked&authors=checked&abstract=checked&sponsors=checked&searchbytag=checked| NA-MIC Publications Database] | |
− | + | = Key Investigators = | |
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* Utah: Tom Fletcher, Saurav Basu, McKay Davis, Ross Whitaker | * Utah: Tom Fletcher, Saurav Basu, McKay Davis, Ross Whitaker | ||
− | + | = Links = | |
− | [[Media:2007_Project_Half_Week_RicianNoiseDTI.ppt| | + | Project Week Results: [[Media:2007_Project_Half_Week_RicianNoiseDTI.ppt|Jan 2007]] |
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Latest revision as of 19:57, 27 November 2007
Home < Projects:DTIRicianNoiseRemovalBack to NA-MIC_Collaborations, Utah Algorithms
DTI Rician Noise Removal
Our Objective is to provide a software tool for clinicians that will filter diffusion tensor images using our Rician noise removal algorithm. The method should be completely automatic and give the user the option of reviewing the images to make sure that the results are acceptable.
Description
Developed a Slicer module for our DT-MRI Rician noise removal during the 2007 Project Half Week. Also enhanced the method by including an automatic method for determining the noise sigma in the image. This makes the algorithm completely automatic, i.e., there are no free parameters. Also, since the module is implemented in Slicer, images can be reviewed directly in the Slicer program after applying the filter.
Publications
Key Investigators
- Utah: Tom Fletcher, Saurav Basu, McKay Davis, Ross Whitaker
Links
Project Week Results: Jan 2007