Difference between revisions of "Link Progress"
From NAMIC Wiki
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; C – Study of limit cases (tract reconstruction issue) : | ; C – Study of limit cases (tract reconstruction issue) : | ||
:* sensitivity to inputs (WM/ROIs) - needing criteria definition and algorythmic extensions as shown on the following example | :* sensitivity to inputs (WM/ROIs) - needing criteria definition and algorythmic extensions as shown on the following example | ||
− | + | {| | |
+ | |[[File:ACC_amy_s1.png]|thumb|400|picA] | ||
+ | |[[File:ACC_amy_s2.png]|thumb|400|picB] | ||
+ | |} | ||
:* further algorythmic extensions if needed for dealing with specific reconstruction cases (tracts with multiple branches) | :* further algorythmic extensions if needed for dealing with specific reconstruction cases (tracts with multiple branches) | ||
:** design of ROI optimization | :** design of ROI optimization |
Revision as of 01:41, 20 April 2009
Home < Link ProgressBack to NA-MIC Collaborations, Harvard DBP 2, DBP2:Harvard:Brain_Segmentation_Roadmap
Stochastic Tractography Progress
Status
Stochastic tractography requires careful maintenance and on-going development improving its usability and performance.
To get the latest module documentation goes on the Slicer 3.4 documentation
- A - Development of tractography workflow
-
- DWI image preprocessing
- denoising
- Eddy currents corrections
- WM mask & ROIs creation
- tensor estimation & visualization
- tracts reconstruction & visualization (should be useful to see tracts and not only the connectivity map)
- connectivity maps creation & visualization
- DWI image preprocessing
- B - Visualization of diffusion properties - test utilities
-
- reveal more features related to diffusion - develop visualization
- finalize batch - testing different parameters of the stochastic tractography with different datasets - wrap up of the results
- C – Study of limit cases (tract reconstruction issue)
-
- sensitivity to inputs (WM/ROIs) - needing criteria definition and algorythmic extensions as shown on the following example
[[File:ACC_amy_s1.png]|thumb|400|picA] | [[File:ACC_amy_s2.png]|thumb|400|picB] |
- further algorythmic extensions if needed for dealing with specific reconstruction cases (tracts with multiple branches)
- design of ROI optimization
- moving ROI
- further algorythmic extensions if needed for dealing with specific reconstruction cases (tracts with multiple branches)
Updates/Progress
- A - Development of tractography workflow
-
- initial skeleton incorporating already existing stochastic tractography components (done)
- test Slicer GUI access with python (done)
- implement tractography algorythm in python (based on Ola Friman Matlab implementation) (done)
- test based on sample dataset show identical computational results between Matlab and python implementation (done)
- multiprocessing (and clustering) supported (done)
- roi filtering from region A to region B and B to A (done)
- module release ready (done)
- bugfix (in progress)
- B - Visualization of diffusion properties
-
- create visual map showing regions defined by WM mask where FA (fractional anisotropy is upper the defined threshold e.g. 0.3) and where the mask forbids (defining as a non white matter region) the stochastic algorythm to go in (done)
- C – Study of limit cases (tract reconstruction issue)
-
- relate C to B
Schedule
- 08/2008 - Introduction to tractography, Slicer software, articles related to tractography.
- 09/2008 - Setup of Slicer3, first tests with stochastic tractography, algorythm implementation, work with training datasets
- 10/2008 - Introduction of python interpreter for implementation of batch utility + diffusion features visualization
- 11/2008 - Completion of batch utility, testing for NAMIC meeting preparation, tractography workflow first prototype ready
- 12/2008 - Wrap up, finalization of NAMIC meeting presentation for the stochastic tractography module
- 04/2009 - Module release ready for Slicer 3.4