2010 Winter Project Week WM ATLAS - Revision history

Lauren: /* Key Investigators */

2010-01-08T17:42:56Z

Key Investigators

2010-01-08T17:40:57Z

2010-01-08T17:40:32Z

2010-01-08T17:39:44Z

2010-01-08T17:37:21Z

Key Investigators

2010-01-08T17:36:36Z

2010-01-08T17:35:46Z

2010-01-08T17:30:33Z

Key Investigators

2010-01-08T17:29:12Z

2010-01-07T20:51:37Z

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 <h3>Progress</h3>
-Our current goal is to decide what dependencies the atlas creation software should have and whether re-implementation in python is feasible.
+We have tested/debugged the group registration and enabled Slicer3 display of matlab output for tract prediction.
 * Preprocessing

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 <gallery>
 Image:PW-SLC2010.png|[[2010_Winter_Project_Week#Projects|Projects List]]
-Image:WM-seg-1.png|Input from example subject: Automatically segmented fiber tracts and fMRI peak locations. Data from 5 subjects has been used in matlab to build a fiber-fMRI distance model to enable prediction/detection of fiber tracts using fMRI.
+Image:WM-seg-1.png|Input from example subject: Automatically segmented fiber tracts and fMRI peak locations. This data from 5 subjects has been used in matlab to build a fiber-fMRI distance model to enable prediction/detection of fiber tracts using fMRI.
 Image:SlicerImage_1.png|Output: Yellow region is prediction of arcuate location in this patient, based on fMRI peaks (spheres). Predicted AF visualized in Slicer3 with fMRI points and actual patient's fiber tracts.
 Image:SlicerImage_0.png|Output: Predicted AF location visualized in Slicer3 with fibers clustered by python test code and colored using Mahnaz Maddah's cluster coloring in Slicer3.

@@ Line 3: / Line 3: @@
 Image:PW-SLC2010.png|[[2010_Winter_Project_Week#Projects|Projects List]]
 Image:WM-seg-1.png|Input from example subject: Automatically segmented fiber tracts and fMRI peak locations. Data from 5 subjects has been used in matlab to build a fiber-fMRI distance model to enable prediction/detection of fiber tracts using fMRI.
-Image:SlicerImage_1.png|Output: Search region for arcuate based on fMRI locations. Yellow region is prediction of arcuate location in this patient. Predicted AF visualized in Slicer3 with fMRI points and actual patient's fiber tracts.
+Image:SlicerImage_1.png|Output: Yellow region is prediction of arcuate location in this patient, based on fMRI peaks (spheres). Predicted AF visualized in Slicer3 with fMRI points and actual patient's fiber tracts.
 Image:SlicerImage_0.png|Output: Predicted AF location visualized in Slicer3 with fibers clustered by python test code and colored using Mahnaz Maddah's cluster coloring in Slicer3.
 </gallery>

@@ Line 2: / Line 2: @@
 <gallery>
 Image:PW-SLC2010.png|[[2010_Winter_Project_Week#Projects|Projects List]]
-Image:WM-seg-1.png|Input from example subject: Automatically segmented fiber tracts and fMRI peak locations.
+Image:WM-seg-1.png|Input from example subject: Automatically segmented fiber tracts and fMRI peak locations. Data from 5 subjects has been used in matlab to build a fiber-fMRI distance model to enable prediction/detection of fiber tracts using fMRI.
 Image:SlicerImage_1.png|Output: Search region for arcuate based on fMRI locations. Yellow region is prediction of arcuate location in this patient. Predicted AF visualized in Slicer3 with fMRI points and actual patient's fiber tracts.
 Image:SlicerImage_0.png|Output: Predicted AF location visualized in Slicer3 with fibers clustered by python test code and colored using Mahnaz Maddah's cluster coloring in Slicer3.

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 * Clustering
 ** initial single-subject cluster test implemented in python
-** communicated with Mahnaz Maddah to learn how to see clusters in Slicer3 (cell data array must be called ClusterId)
+** communicated with Mahnaz Maddah to learn how to display clusters in Slicer3 (cell data array must be called ClusterId)
 * IGT fMRI+DTI atlas
 ** Initial methods development: fiber-fMRI distance model (MICCAI Diffusion workshop 2009)
-** Output of matlab-generated tract predictions to slicer3
+** Output of matlab-generated tract predictions to slicer3 as nrrd volumes
 </div>
 </div>

@@ Line 5: / Line 5: @@
 Image:Predict-AG_1124-3.png|Output: Search region for arcuate based on fMRI locations. Yellow region is prediction of arcuate location in this patient.
 Image:SlicerImage_1.png|Output: Predicted AF location visualized in Slicer3 with fMRI points and actual patient's fiber tracts.
 </gallery>

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 ==Key Investigators==
-* Lauren O'Donnell (Instructor, Harvard Medical School (BWH))
+* Lauren O'Donnell (Harvard Medical School (BWH))
 * Carl-Fredrik Westin (Professor, Harvard Medical School (BWH) )
 * William Wells (Professor, Harvard Medical School (BWH) )
@@ Line 57: / Line 58: @@
 * Preprocessing
-** initial implementation of BatchMake modules for tensor calc, but found ipython is preferable for overall pipeline
+** Debugging of ITK congealing with Luis.
 ** implementation of initial seeding pipeline script in ipython
 ** Gordon has implemented tractography methods and some probing capability in teem, may allow more direct teem/itk/vtk dependencies
 * Clustering
-** looking into available packages in python
+** initial single-subject cluster test implemented in python
 * IGT fMRI+DTI atlas
 ** Initial methods development: fiber-fMRI distance model (MICCAI Diffusion workshop 2009)
 </div>
 </div>