2011 Winter Project Week:LandmarkRegularization - Revision history

Nsh: /* Key Investigators */

2011-01-14T15:31:22Z

Key Investigators

Nsh at 15:26, 14 January 2011

2011-01-14T15:26:12Z

Nsh: /* Key Investigators */

2011-01-13T23:20:38Z

Key Investigators

Nsh at 22:37, 13 January 2011

2011-01-13T22:37:58Z

Nsh: /* Key Investigators */

2011-01-10T18:28:33Z

Key Investigators

Nsh at 18:27, 10 January 2011

2011-01-10T18:27:05Z

Nsh at 21:47, 23 December 2010

2010-12-23T21:47:27Z

Nsh at 21:46, 23 December 2010

2010-12-23T21:46:37Z

Nsh at 21:35, 23 December 2010

2010-12-23T21:35:30Z

Nsh at 21:29, 23 December 2010

2010-12-23T21:29:26Z

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 <h3>Progress</h3>
-We have implemented LANDWARP Landmark deformable registration command line module. It appears under All modules/Plastimatch as Input/Output panel. There you choose Fixed Volume which is a reference image, Moving Volume which is a test image that will be warped to match the reference image.  Fixed Fiducials and Moving Fiducials which are fidicial lists you created for reference and test image respectively. Output Volume is where the warped image will be placed (you can create new or overwrite existing image). Then you can choose a type of landmark based algorithm, "tps" for global registration ot "gauss" for local registration. Local registration requires RBF radius, Stiffness and Default Pixel Value which by default are 50 mm, 0, and -1000, respectively. After you hit Apply the warped image will appear automatically in Slicer window.
+We have implemented LANDWARP Landmark deformable registration command line module. It appears under All modules/Plastimatch as Input/Output panel. There you choose Fixed Volume which is a reference image, Moving Volume which is a test image that will be warped to match the reference image. You also choose Fixed Fiducials and Moving Fiducials which are fidicial lists you created for reference and test image respectively. Output Volume is where the warped image will be placed (you can create new or overwrite existing image). Then you can choose a type of landmark based algorithm, "tps" for global registration or "gauss" for local registration. Local registration requires RBF radius, Stiffness and Default Pixel Value which by default are 50 mm, 0, and -1000, respectively. After you click Apply button and wait until registration is done, the warped image will appear automatically in Slicer window.
 </div>
 </div>

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 __NOTOC__
 <gallery>
-File:na-mic0.png|
+File:na-mic0.png|Slecer 3.6 panel
-File:na-mic1.png|
+File:na-mic1.png|Input reference image
-File:na-mic2.png|
+File:na-mic2.png|Input test image
-File:na-mic3.png
+File:na-mic3.png|Output warped image
 </gallery>
 <gallery>
-File:na-mic4.png|
+File:na-mic4.png|Input reference image
-File:na-mic5.png|
+File:na-mic5.png|Input test image
-File:na-mic6.png|
+File:na-mic6.png|Output warped image without regularization
-File:na-mic7.png
+File:na-mic7.png|Output warped image with regularization
 </gallery>

@@ Line 47: / Line 47: @@
 <h3>Progress</h3>
 </div>
 </div>

@@ Line 1: / Line 1: @@
 __NOTOC__
 <gallery>
-File:Synth1.png|Reference image
+File:na-mic0.png|
-File:Synth2.png|Test image
+File:na-mic1.png|
-File:Synth3.png|Result of automatic registration
+File:na-mic2.png|
 </gallery>
 <gallery>
-File:Synth4.png|Enhancement with one landmark
+File:na-mic4.png|
-File:Synth5.png|Enhancement with two landmarks
+File:na-mic5.png|
-File:Synth6.png|Enhancement with three landmarks
+File:na-mic6.png|
 </gallery>

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 We use Gaussian radial basis functions (RBFs)
 to define a vector field from point landmarks,
-and applies regularization based on the vector field second order derivative.
+and apply regularization based on the vector field second order derivative.
 </div>

@@ Line 23: / Line 23: @@
 <h3>Objective</h3>
-We are introducing a new approach for landmark-based
+We are introducing a new method for local enhancement of image registration. The method is intended to make rapid, interactive corrections of local registration failures with a small number of mouse clicks.
-deformable image registration.  Our method uses
+We use Gaussian radial basis functions (RBFs)
 to define a vector field from point landmarks,
 and applies regularization based on the vector field second order derivative.
@@ Line 40: / Line 39: @@
 approaches such as Wendland functions, because the
 regularized vector field can be solved exactly with a simple equation.
-Our plan for the project week is to implement our registration algorithm as a Slicer plugin.
+Algorithm for the landmark-based registration has been implemented as a part of out in-house software Plastimatch. We have validated the method on 10 large landmark sets. This work has been submitted for publication to IEEE Transactions on Medical Imaging.
 </div>
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 <h3>Progress</h3>
 </div>
 </div>

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 </gallery>
-<gallery>
+[[File:head1.png|200px]]
-File:head1.png
+[[File:head2.png|200px]]