2010 Winter Project Week Tractography - Revision history

Malcolm: status update

2010-01-08T15:46:15Z

status update

2010-01-04T19:29:28Z

2010-01-04T16:39:42Z

2009-12-03T22:18:53Z

2009-12-02T01:42:22Z

Key Investigators

2009-12-02T01:27:13Z

Key Investigators

2009-12-02T01:26:34Z

Key Investigators

2009-12-02T01:25:52Z

Key Investigators

2009-12-02T01:24:09Z

Key Investigators

2009-12-02T01:21:53Z

Key Investigators

@@ Line 19: / Line 19: @@
 <div style="width: 27%; float: left; padding-right: 3%">
 <h3>Progress</h3>
-We have MATLAB implementations of various local models (single-tensor, two-tensor, Watson functions, weighted mixtures of these, etc.) and various model-based filters (Kalman, unscented Kalman, particle, etc.).  We have begun converting these to NumPy/Python as well as the additional infrastructure for performing tractography within Slicer.
+We have Python/NumPy implementations of various local models (single-tensor, two-tensor, Watson functions, weighted mixtures of these, etc.) and various model-based filters (Kalman, unscented Kalman, particle, etc.) and deterministic tractography infrastructure.
 </div>

@@ Line 2: / Line 2: @@
 <gallery>
 Image:PW-SLC2010.png|[[2010_Winter_Project_Week#Projects|Projects List]]
-</gallery>[[File:Filtered_tractography.png|600px]]
+Image:Filtered_tractography.png|Left hemisphere
 ==Key Investigators==

@@ Line 2: / Line 2: @@
 <gallery>
 Image:PW-SLC2010.png|[[2010_Winter_Project_Week#Projects|Projects List]]
-</gallery>
+</gallery>[[File:Filtered_tractography.png|600px]]
 ==Key Investigators==

@@ Line 14: / Line 14: @@
 <div style="width: 27%; float: left; padding-right: 3%">
 <h3>Plan</h3>
-Implement various local models and filtering techniques.  Support both region-of-interest and fiducial seeding.  Support both interactive and batch processing.</div>
+Implement various local models and filtering techniques.  Support both region-of-interest and fiducial seeding.  Support both interactive and batch processing.  Picking fibers and moving them between polydata structures.</div>
 <div style="width: 27%; float: left; padding-right: 3%">

@@ Line 5: / Line 5: @@
 ==Key Investigators==
-* BWH: Peter Savadjiev, James Malcolm, Yogesh Rathi, C-F Westin
+* BWH: James Malcolm, Peter Savadjiev, Yogesh Rathi, C-F Westin
 <div style="margin: 20px;">
@@ Line 23: / Line 23: @@
 <p>
 <div style="width: 97%; float: left; padding-right: 3%">
 # Malcolm, Michailovich, Bouix, Westin, Shenton, Rathi. "A filtered approach to neural tractography using the Watson directional function", MedIA 14(1), p.58-69, 2010.
 # Malcolm, Shenton, Rathi. "Neural tractography using an unscented Kalman filter", IPMI, p.126-138, 2009.
 </div>

@@ Line 25: / Line 25: @@
 # Savadjiev, Campbell, Pike, Siddiqi. "3D Curve Inference for Diffusion MRI Regularization and Fibre Tractography", MedIA 10(5), p.799-813, 2006.
 # Malcolm, Michailovich, Bouix, Westin, Shenton, Rathi. "A filtered approach to neural tractography using the Watson directional function", MedIA 14(1), p.58-69, 2010.
-# Malcolm, Shenton, Rathi. "Neural Tractography using an unscented Kalman filter", IPMI, p.126-138, 2009.
+# Malcolm, Shenton, Rathi. "Neural tractography using an unscented Kalman filter", IPMI, p.126-138, 2009.
 </div>

@@ Line 10: / Line 10: @@
 <div style="width: 27%; float: left; padding-right: 3%">
 <h3>Objective</h3>
-Integrate recent methods for filtered tractography into Slicer3 using Python</div>
+Integrate recent methods for filtered tractography into Slicer3 using Python.</div>
 <div style="width: 27%; float: left; padding-right: 3%">
 <h3>Approach, Plan</h3>
-Implement various local models and filtering techniques.  Support both region-of-interest and fiducial seeding.</div>
+Implement various local models and filtering techniques.  Support both region-of-interest and fiducial seeding.  Support both interactive and batch processing.</div>
 <div style="width: 27%; float: left; padding-right: 3%">
 <h3>Progress</h3>
-We have MATLAB implementations of various local models (single-tensor, two-tensor, Watson functions, weighted mixtures of these, etc.) and various model-based filters (Kalman, unscented Kalman, particle, etc.).  We have begun converting these to NumPy/Python as well as the additional infrastructure for performing tractography.
+We have MATLAB implementations of various local models (single-tensor, two-tensor, Watson functions, weighted mixtures of these, etc.) and various model-based filters (Kalman, unscented Kalman, particle, etc.).  We have begun converting these to NumPy/Python as well as the additional infrastructure for performing tractography within Slicer.
 </div>

@@ Line 20: / Line 20: @@
 We have MATLAB implementations of various local models (single-tensor, two-tensor, Watson functions, weighted mixtures of these, etc.) and various model-based filters (Kalman, unscented Kalman, particle, etc.).  We have begun converting these to NumPy/Python as well as the additional infrastructure for performing tractography.
 </div>
-<br>
-<div style="width: 97%">
+<p>
 # Savadjiev, Campbell, Pike, Siddiqi "3D Curve Inference for Diffusion MRI Regularization and Fibre Tractography", MedIA 10(5), p.799-813, 2006.
 # Malcolm, Michailovich, Bouix, Westin, Shenton, Rathi, "A filtered approach to neural tractography using the Watson directional function", MedIA 14(1), p.58-69, 2010.
 # Malcolm, Shenton, Rathi, "Neural Tractography using an unscented Kalman filter", IPMI, p.126-138, 2009.
 </div>