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| | __NOTOC__ | | __NOTOC__ |
| | <gallery> | | <gallery> |
| − | Image:PW-SLC2011.png|[[2011_Winter_Project_Week#Projects|Projects List]] | + | Image:PW-MIT2013.png|[[2013_Summer_Project_Week#Projects|Projects List]] |
| − | Image:genuFAp.jpg|Scatter plot of the original FA data through the genu of the corpus callosum of a normal brain.
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| − | Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
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| | </gallery> | | </gallery> |
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| − | ==Instructions for Use of this Template==
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| − | #Please create a new wiki page with an appropriate title for your project using the convention Project/<Project Name>
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| − | #Copy the entire text of this page into the page created above
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| − | #Link the created page into the list of projects for the project event
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| − | #Delete this section from the created page
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| − | #Send an email to tkapur at bwh.harvard.edu if you are stuck
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| | ==Key Investigators== | | ==Key Investigators== |
| − | * BWH: Antonio Tristán-Vega, Demian Wasserman, Carl-Fredrik Westin | + | * GRC: Rui Li, Jim Miller |
| | + | * Kitware: Jean-Christophe Fillion-Robin |
| | + | * Isomics: Steve Pieper |
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| | <div style="margin: 20px;"> | | <div style="margin: 20px;"> |
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| | <h3>Objective</h3> | | <h3>Objective</h3> |
| − | In the last project week we delivered an implementation of the Finsler method to compute the connectivity among regions in the white matter through High Angular Resolution Diffusion Imaging. Such method provides a costs map from a given seeding point/region to any other point within the brain. The aim in this project is tracing the minimum cost paths between two given regions in the white matter, which will in turn provide the desired streamlines.
| + | Python embedding library to manage calling python functions from C++. This will eliminate the code duplication in Slicer. |
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| | <h3>Approach, Plan</h3> | | <h3>Approach, Plan</h3> |
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| − | The method is described in detail in the references below. To compute the costs map we use the Fast Sweeping algorithm: upon convergence, this method provides the minimum cost at each image voxel together with the direction such cost was reached from. Thus, the "backtracing" of these directions from a given point to the seeding point/region provides the minimum cost path.
| + | Discuss with Jc and Steve regarding how to incorporate into Slicer. Currently it |
| | + | is used as a downloadable library during superbuild, similar to SlicerExecutionModel. |
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| | </div> | | </div> |
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| | <h3>Progress</h3> | | <h3>Progress</h3> |
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| − | By this time the following code available in C++/ITK:
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| − | * HARDI estimation based on Spherical Harmonics (to compute Finsler local costs).
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| − | * Parallel fast sweeping algorithm (to compute the globally optimal costs).
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| − | * Slicer module implementing the computation of the costs map and arrival directions from input DWI data.
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| | </div> | | </div> |
| | </div> | | </div> |
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| − | <div style="width: 97%; float: left;">
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| | ==Delivery Mechanism== | | ==Delivery Mechanism== |
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| − | This work will be delivered to the NA-MIC Kit as a Slicer Module
| + | https://github.com/grclirui/PythonCppAPI.git |
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| − | ==References==
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| − | * Melonakos, J.; Pichon, E.; Angenent, S.; Tannenbaum, A.; "Finsler active contours." IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(3): 412-423, 2008.
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| − | * Melonakos, J.; Mohan, V.; Niethammer, M.; Smith, K.; Kubicki M.; Tannenbaum, A.; "Finsler tractography for white matter connectivity analysis of the cingulum bundle", Procs. MICCAI 2007, LNCS 4791, pp. 36-43.
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| − | </div>
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