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− | ===Module Name===
| + | <big>'''Note:''' We are migrating this content to the slicer.org domain - <font color="orange">The newer page is [https://www.slicer.org/wiki/Slicer3:Module:Rician_Noise_Removal here]</font></big> |
− | Rician Noise Removal in Diffusion Tensor MRI
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− | {|
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− | |[[Image:screenshotBlank.png|thumb|280px|Caption 1]]
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− | |[[Image:screenshotBlank.png|thumb|280px|Caption 2]]
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− | |[[Image:screenshotBlank.png|thumb|280px|Caption 3]]
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− | |}
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− | | |
− | == General Information ==
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− | ===Module Type & Category===
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− | Type: CLI
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− | Category: Filtering DWI and tensors
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− | ===Authors, Collaborators & Contact===
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− | * Saurav Basu: University of Utah
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− | * Thomas Fletcher, University of Utah
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− | * Ross Withaker, University of Utah
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− | * Contact: Thomas Fletcher
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− | | |
− | ===Module Description===
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− | Rician noise introduces a bias into MRI measurements that
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− | can have a significant impact on the shapes and orientations of ten-
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− | sors in diffusion tensor magnetic resonance images. This is less of a
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− | problem in structural MRI, because this bias is signal dependent and
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− | it does not seriously impair tissue identification or clinical diagnoses.
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− | However, diffusion imaging is used extensively for quantitative evalua-
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− | tions, and the tensors used in those evaluations are biased in ways that
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− | depend on orientation and signal levels. This paper presents a strat-
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− | egy for filtering diffusion tensor magnetic resonance images that ad-
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− | dresses these issues. The method is a maximum a posteriori estima-
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− | tion technique that operates directly on the diffusion weighted images
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− | and accounts for the biases introduced by Rician noise. We account for
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− | Rician noise through a data likelihood term that is combined with a
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− | spatial smoothing prior. The method compares favorably with several
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− | other approaches from the literature, including methods that filter dif-
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− | fusion weighted imagery and those that operate directly on the diffusion
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− | tensors.
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− | == Usage ==
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− | ===DWI filtering===
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− | ====Examples, Use Cases & Tutorials====
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− | USAGE:dwiFilter <arguments>
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− | Arguments:
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− | 1. Input File Name
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− | 2. Output File Name
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− | 3. NumIterations
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− | 4. Conductance
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− | 5. TimeStep
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− | 6. Filter Type : (Simple Aniso-0,Chi Squared-1,Rician-2,Gaussian-3)
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− | 7. Sigma for bias correction
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− | 8. Lamda (Rician Correction Term)
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− | 9. Lamda (Gaussian Correction Term)
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− | Argument Description:
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− | <Input File Name>
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− | Name of the DWI file to be filtered. For example
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− | <noisyDWI_10.nhdr> is a noisy DWI file provided | |
− | in the data directory. It was generated by adding
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− | synthetic Rician noise with a sigma=10 to a cleanDWI.nhdr
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− | <Output File Name>
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− | Name of the filtered DWI file. For example
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− | <filteredDWI.nhdr>
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− | <NumIterations>
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− | Number of iterations you want to run the filter for.
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− | <Conductance>
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− | The value of the conductance term in anisotropic
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− | diffusion filtering (Ex: 1.0)
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− | Note: Large Conductance will oversmooth the image
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− | It is important to tune the conductance to obtain
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− | best results.
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− | <Time Step>
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− | This determines the step size in the gradient
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− | descent. It can be atmost 0.0625.
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− | <Filter Type>
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− | Can Take 3 values:
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− | 0 means perform simple anisotropic diffusion
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− |
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− | 1 means perform Chi-Squared smoothing (square the image and
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− | perform anisotropic diffusion and then subtract the variance
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− | of the noise, and take square root. (The square of a Rice
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− | distribution is a Chi Squared distribution with known bias
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− | equal to the variance of the noise)
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− | (Refer:Max Likelihood Est. of Rician Ditribution Parameters.
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− | Sijbers et. al)
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− | 2 means Perform Rician bias correction filtering.
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− | (Refer: Rician Noise Removal in DT-MRI.)
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− | 3 is same as 2 except use a Gaussian Attachment Term .
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− | <Sigma>
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− | Estimate of noise in the data.
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− | This can be done by squaring the airvoxels
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− | in the real data. The sum of square of all
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− | the intensities in the air region should equal
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− | 2*variance of the noise in the data.
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− | (Sijbers et. al)
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− | <lamda1, lamda2>
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− | The weights for the Rician and Gaussian
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− | attachment terms.
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− | EXAMPLE
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− | -------------
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− | dwiFilter ../data/noisyDWI_10.nhdr filteredDWI.nhdr 1 1.0 0.0625 2 10 100 0
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− | Filters the noisyDWI_10.nhdr for 1 iteration with a conductance of 1.0
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− | timeStep 0.0625 using Rician filtering with a Rician attachement term
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− | weight of 100. The estimate of noise in the input image is a sigma of 10
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− | The filtered image is filteredDWI.nhdr.
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− | * Note use cases for which this module is especially appropriate, and/or link to examples.
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− | * Link to examples of the module's use
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− | * Link to any existing tutorials
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− | | |
− | ===Quick Tour of Features and Use===
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− | List all the panels in your interface, their features, what they mean, and how to use them. For instance:
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− | * '''Input panel:'''
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− | * '''Parameters panel:'''
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− | * '''Output panel:'''
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− | * '''Viewing panel:'''
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− | == Development ==
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− | ===Dependencies===
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− | Other modules or packages that are required for this module's use.
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− | ===Known bugs===
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− | Follow this link to the Slicer3 bug tracker:
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− | http://na-mic.org/Mantis/main_page.php
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− | ===Usability issues===
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− | Follow this link to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing:
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− | http://na-mic.org/Mantis/main_page.php
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− | ===Source code & documentation=== | |
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− | Customize following links for your module:
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− | http://www.na-mic.org/ViewVC/index.cgi/
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− | Links to documentation generated by doxygen:
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− | http://www.na-mic.org/Slicer/Documentation/Slicer3/html/
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− | == More Information ==
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− | ===Acknowledgement===
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− | Include funding and other support here.
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− | ===References===
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− | Publications related to this module go here. Links to pdfs would be useful.
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