Difference between revisions of "Link Progress"
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− | Back to [[NA-MIC_Internal_Collaborations|NA-MIC Collaborations]], [[DBP2:Harvard|Harvard DBP 2]] | + | Back to [[NA-MIC_Internal_Collaborations|NA-MIC Collaborations]], [[DBP2:Harvard|Harvard DBP 2]], [[DBP2:Harvard:Brain_Segmentation_Roadmap]] |
+ | |||
__NOTOC__ | __NOTOC__ | ||
=Stochastic Tractography Progress= | =Stochastic Tractography Progress= | ||
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Stochastic tractography requires careful maintenance and on-going development improving its usability and performance. | Stochastic tractography requires careful maintenance and on-going development improving its usability and performance. | ||
+ | |||
+ | To get the latest module documentation goes on the [https://www.slicer.org/wiki/Modules:StochasticTractography-Documentation-3.4 Slicer 3.4 documentation] | ||
; A - Development of tractography workflow : | ; A - Development of tractography workflow : | ||
− | :* DWI image | + | :* DWI image preprocessing (summer week 2009 project) |
− | :* WM mask & ROIs creation | + | :** denoising (Rician) - currently Gaussian (FWHM = Full Width Half Maximum) |
− | :* tensor estimation & visualization ( | + | :** Eddy currents corrections |
− | :* tracts reconstruction & visualization ( | + | :** EPI distortion correction |
− | :* connectivity maps creation & visualization | + | :* WM mask & ROIs creation (integrated) |
+ | :* tensor estimation & visualization (integrated) | ||
+ | :* tracts reconstruction & visualization (integrated) | ||
+ | :* connectivity maps creation & visualization (integrated) | ||
; B - Visualization of diffusion properties - test utilities : | ; B - Visualization of diffusion properties - test utilities : | ||
Line 18: | Line 24: | ||
; C – Study of limit cases (tract reconstruction issue) : | ; C – Study of limit cases (tract reconstruction issue) : | ||
− | :* sensitivity to inputs (WM/ROIs) | + | :* transformation issues between 3 spaces (IJK, RAS, measurement frame) |
− | :* further algorythmic extensions if needed for dealing with specific reconstruction cases | + | {| |
− | + | |[[File:helix_withsmoothing.png|thumb|400px|Reconstruction of helix]] | |
+ | |} | ||
+ | |||
+ | :* optimal parameter setting e.g. number of path per voxel | ||
+ | {| | ||
+ | |[[File:arcu_1path.png|thumb|400px|Arcuate reconstruction with only 1 path per voxel]] | ||
+ | |} | ||
+ | |||
+ | :* reduction of sparse density/connectivity map with noisy dataset (1.5 Tesla) | ||
+ | {| | ||
+ | |[[File:cingul.png|thumb|400px|Density map for cingulum based on 1.5 Tesla scan]] | ||
+ | |} | ||
+ | |||
+ | :* sensitivity to inputs (WM/ROIs) - needing criteria definition and algorythmic extensions as shown on the following example | ||
+ | {| | ||
+ | |[[File:ACC_amy_s4.png|thumb|400px|No connection with restrictive white matter mask and misregistered ROIS (left sagittal view)]] | ||
+ | |[[File:ACC_amy_s3.png|thumb|400px|Connection appears when ROI vicinity and brain mask (notion of unrestrictive 'white matter' mask) are applied (left sagittal view)]] | ||
+ | |} | ||
+ | {| | ||
+ | |[[File:ACC_amy_s1.png|thumb|400px|No connection with restrictive white matter mask and misregistered ROIS (left superior view)]] | ||
+ | |[[File:ACC_amy_s2.png|thumb|400px|Connection appears when ROI vicinity and brain mask (notion of unrestrictive 'white matter' mask) are applied (left superior view)]] | ||
+ | |} | ||
+ | |||
+ | :* further algorythmic extensions if needed for dealing with specific reconstruction cases | ||
+ | :** ROI optimization | ||
+ | :** moving ROI | ||
== Updates/Progress == | == Updates/Progress == | ||
; A - Development of tractography workflow : | ; 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 for release 3.4 (done) | ||
; B - Visualization of diffusion properties : | ; 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) : | ; C – Study of limit cases (tract reconstruction issue) : | ||
− | :* | + | :* relate C to B |
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* '''08/2008''' - Introduction to tractography, Slicer software, articles related to tractography. | * '''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 | + | * '''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 | * '''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 | * '''11/2008''' - Completion of batch utility, testing for NAMIC meeting preparation, tractography workflow first prototype ready | ||
− | * '''12/2008''' - | + | * '''12/2008''' - Wrap up, finalization of NAMIC meeting presentation for the stochastic tractography module |
+ | * '''04/2009''' - Module release ready for Slicer 3.4 | ||
+ | |||
+ | |||
[[Category: Schizophrenia]] [[Category: Diffusion MRI]] [[Category: Segmentation]] | [[Category: Schizophrenia]] [[Category: Diffusion MRI]] [[Category: Segmentation]] |
Latest revision as of 18:07, 10 July 2017
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 (summer week 2009 project)
- denoising (Rician) - currently Gaussian (FWHM = Full Width Half Maximum)
- Eddy currents corrections
- EPI distortion correction
- WM mask & ROIs creation (integrated)
- tensor estimation & visualization (integrated)
- tracts reconstruction & visualization (integrated)
- connectivity maps creation & visualization (integrated)
- DWI image preprocessing (summer week 2009 project)
- 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)
-
- transformation issues between 3 spaces (IJK, RAS, measurement frame)
- optimal parameter setting e.g. number of path per voxel
- reduction of sparse density/connectivity map with noisy dataset (1.5 Tesla)
- sensitivity to inputs (WM/ROIs) - needing criteria definition and algorythmic extensions as shown on the following example
- further algorythmic extensions if needed for dealing with specific reconstruction cases
- ROI optimization
- moving ROI
- further algorythmic extensions if needed for dealing with specific reconstruction cases
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 for release 3.4 (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 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