UNC MANCOVA Tutorial - Revision history

L.bompard: /* Tutorials */

2011-06-21T19:15:05Z

Tutorials

L.bompard at 18:32, 3 June 2011

2011-06-03T18:32:11Z

L.bompard at 18:30, 3 June 2011

2011-06-03T18:30:24Z

L.bompard at 18:27, 3 June 2011

2011-06-03T18:27:21Z

L.bompard at 18:27, 3 June 2011

2011-06-03T18:27:01Z

L.bompard: /* Overview */

2011-06-03T18:26:48Z

Overview

L.bompard: Created page with '= shapeAnalysisMANCOVA_Wizard= ==Overview== shapeAnalysisMANCOVA offers statistical shape analysis based on a parametric boundary description (SPHARM) as the point-based model …'

2011-06-03T18:25:12Z

Created page with '= shapeAnalysisMANCOVA_Wizard= ==Overview== shapeAnalysisMANCOVA offers statistical shape analysis based on a parametric boundary description (SPHARM) as the point-based model …'

New page

= shapeAnalysisMANCOVA_Wizard=

==Overview==

shapeAnalysisMANCOVA offers statistical shape analysis based on a parametric boundary description (SPHARM) as the point-based model computing method. The point-based models will be analyzed with the methods here proposed using multivariate analysis of covariance (MANCOVA). Here, the number of variates being tested is the dimensionality of our observations. Each point of these observations is a three dimensional displacement vector from the mean. The number of contrasts is the number of equations involved in the null-hypothesis. In order to encompass varying numbers of variates and contrasts, and to account for independent variables, a matrix computation is performed. This matrix represents the multidimensional aspects of the correlation significance and it can be transformed into a scalar measure by manipulation of its eigenvalues.

* '''Step by step analysis''': With the ShapeAnalysisMANCOVA_Wizard tutorial, you will learn how to use a graphic interface to load meshes, run a group test in order to get statistical results, displayed through MRML scene.

==Tutorials==

'''shapeAnalysisMANCOVA_Wizard tutorial''' : to perform statistical shape analysis.[[Media:ShapeAnalysisMANCOVA Wizard-Tutorial.ppt|‏ [ppt]]][[Media:shapeAnalysisMANCOVA_Wizard-Tutorial.pdf|‏ [pdf]]]

==Software==

[http://www.slicer.org/pages/Downloads Slicer3.6.3]

[http://www.nitrc.org/frs/?group_id=308 Slicer3 External modules -including BatchMake Description files]

==Tutorial materials==

'''ShapeAnalysisMANCOVA_Wizard data ''': ''NB: You can also use the output file of ShapeAnalysisModule.''
* [http://www.nitrc.org/docman/index.php?group_id=294&selected_doc_group_id=1966&language_id=1#folder Link to NITRC ]
* or directly here :[[Media:ShapeAnalysisMANCOVA_WizardTutorialData_TutorialContestSummer2011.zip|‏ ShapeAnalysisMANCOVA_WizardTutorialData_TutorialContestSummer2011.zip]]

==Complementary documentation==

* Paniagua B., Styner M., Macenko M., Pantazis D., Niethammer M, Local Shape Analysis using MANCOVA, Insight Journal, 2009 July-December, http://hdl.handle.net/10380/3124

==People==
Lucile Bompard
<br>Clement Vachet
<br>Beatriz Paniagua
<br>Martin Styner

==[http://wiki.na-mic.org/Wiki/index.php/Summer_2011_Tutorial_Contest Back to tutorial contest]==

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	= shapeAnalysisMANCOVA_Wizard=		= shapeAnalysisMANCOVA_Wizard=

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	= shapeAnalysisMANCOVA_Wizard=		= shapeAnalysisMANCOVA_Wizard=

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	* '''Step by step analysis''': With this tutorial you will learn how to run shapeAnalysisMANCOVA using shapeAnalysisMANCOVA_Wizard tutorial. With this graphic interface, you will be able to load meshes, run a group test in order to get statistical results, displayed through MRML scene.		* '''Step by step analysis''': With this tutorial you will learn how to run shapeAnalysisMANCOVA using shapeAnalysisMANCOVA_Wizard tutorial. With this graphic interface, you will be able to load meshes, run a group test in order to get statistical results, displayed through MRML scene.
		+

	==Tutorials==		==Tutorials==

@@ Line 12: / Line 12: @@
 ==Tutorials==
-'''shapeAnalysisMANCOVA_Wizard tutorial''' :  to perform statistical shape analysis.[[Media:ShapeAnalysisMANCOVA Wizard-Tutorial.ppt|‏ [ppt]]][[Media:shapeAnalysisMANCOVA_Wizard-Tutorial.pdf|‏ [pdf]]]
+'''shapeAnalysisMANCOVA_Wizard tutorial''' :  to perform statistical shape analysis.[[Media:ShapeAnalysisMANCOVA WizardTutorial.ppt|‏ [ppt]]][[Media:shapeAnalysisMANCOVA_WizardTutorial.pdf|‏ [pdf]]]
 ==Software==

@@ Line 25: / Line 25: @@
 * [http://www.nitrc.org/docman/index.php?group_id=294&selected_doc_group_id=1966&language_id=1#folder Link to NITRC ]
 * or directly here :[[Media:ShapeAnalysisMANCOVA_WizardTutorialData_TutorialContestSummer2011.zip|‏ ShapeAnalysisMANCOVA_WizardTutorialData_TutorialContestSummer2011.zip]]
 ==Complementary documentation==

@@ Line 5: / Line 5: @@
 shapeAnalysisMANCOVA offers statistical shape analysis based on a parametric boundary description (SPHARM) as the point-based model computing method. The point-based models will be analyzed with the methods here proposed using multivariate analysis of covariance (MANCOVA). Here, the number of variates being tested is the dimensionality of our observations. Each point of these observations is a three dimensional displacement vector from the mean. The number of contrasts is the number of equations involved in the null-hypothesis. In order to encompass varying numbers of variates and contrasts, and to account for independent variables, a matrix computation is performed. This matrix represents the multidimensional aspects of the correlation significance and it can be transformed into a scalar measure by manipulation of its eigenvalues.
-* '''Step by step analysis''': With the ShapeAnalysisMANCOVA_Wizard tutorial, you will learn how to use a graphic interface to load meshes, run a group test in order to get statistical results, displayed through MRML scene.
+* '''Step by step analysis''': With this tutorial you will learn how to run shapeAnalysisMANCOVA using shapeAnalysisMANCOVA_Wizard tutorial. With this graphic interface, you will be able to load meshes, run a group test in order to get statistical results, displayed through MRML scene.
 ==Tutorials==