Difference between revisions of "Link Progress"
From NAMIC Wiki
Line 9: | Line 9: | ||
; A - Development of tractography workflow : | ; A - Development of tractography workflow : | ||
:* DWI image preprocessing | :* DWI image preprocessing | ||
− | + | :** denoising | |
− | + | :** Eddy currents corrections | |
:* WM mask & ROIs creation | :* WM mask & ROIs creation | ||
:* tensor estimation & visualization (this step is somewhat hidden) | :* tensor estimation & visualization (this step is somewhat hidden) | ||
Line 30: | Line 30: | ||
:* test Slicer GUI access with python (done) | :* test Slicer GUI access with python (done) | ||
:* implement tractography algorythm in python (based on Ola Friman Matlab implementation) (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) | |
; B - Visualization of diffusion properties : | ; B - Visualization of diffusion properties : |
Revision as of 15:48, 3 November 2008
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.
- A - Development of tractography workflow
-
- DWI image preprocessing
- denoising
- Eddy currents corrections
- WM mask & ROIs creation
- tensor estimation & visualization (this step is somewhat hidden)
- 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) if exist - needing criteria definition and algorythmic extensions
- 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 (in progress)
- 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)
- 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 algorithm to go in
- 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, 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