SciVisFall2007/Assignment 4 - Revision history

Cscheid: /* Assignment 4a: DTI Visualization */

2007-12-08T21:46:45Z

Assignment 4a: DTI Visualization

← Older revision		Revision as of 21:46, 8 December 2007
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	The first part of the assignment is to perform some basic visualizations of diffusion tensor data. Because this is the final assignment, it will be a little more difficult because there are no examples given. It also combines many of the techniques covered in other assignments such as color mapping, isosurfacing, glyph visualization, and streamlines.		The first part of the assignment is to perform some basic visualizations of diffusion tensor data. Because this is the final assignment, it will be a little more difficult because there are no examples given. It also combines many of the techniques covered in other assignments such as color mapping, isosurfacing, glyph visualization, and streamlines.

	This is a diffusion tensor dataset [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbh.vtk gktbh.vtk], and a corresponding anisotropy volume [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbhFA.vtk gktbhFA.vtk]. These volumes cover the right half of a [http://www.cs.utah.edu/~gk Gordon Kindlmann's] brain. They encode information about the structure of the brain matter. The anisotropy volume has high values in regions which are likely white matter in the brain, and these are the regions of interest.		This is a diffusion tensor dataset [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbh.vtk gktbh.vtk], and a corresponding anisotropy volume [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbhFA.vtk gktbhFA.vtk]. These volumes cover the right half of [http://www.cs.utah.edu/~gk Gordon Kindlmann's] brain. They encode information about the structure of the brain matter. The anisotropy volume has high values in regions which are likely white matter in the brain, and these are the regions of interest.

Stevec at 18:02, 4 December 2007

2007-12-04T18:02:33Z

← Older revision		Revision as of 18:02, 4 December 2007
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	The assignment is due at midnight on December ~~??th~~.		The assignment is due at midnight on December 15th.
	The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.		The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.

Stevec at 00:13, 4 December 2007

2007-12-04T00:13:42Z

← Older revision		Revision as of 00:13, 4 December 2007
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	The assignment is due at midnight on December ~~11th~~.		The assignment is due at midnight on December ??th.
	The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.		The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.

Stevec: /* Assignment 4b: Graph Visualization */

2007-12-01T19:55:31Z

Assignment 4b: Graph Visualization

← Older revision		Revision as of 19:55, 1 December 2007
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	The goal of this assignement is to compare several different InfoVis graph layout strategies. InfoVis capabilities in VTK are very new (ie., unstable) and some of the features do not work to well, or crash (I recommend saving often). Thus, this assignment will be somewhat limited in what we can do. The graph we will be visualizing is the vtk class hierarchy, generated on-the-fly using a PythonSource and Python's introspection capabilities.		The goal of this assignement is to compare several different InfoVis graph layout strategies. InfoVis capabilities in VTK are very new (ie., unstable) and some of the features do not work to well, or crash (I recommend saving often). Thus, this assignment will be somewhat limited in what we can do. The graph we will be visualizing is the vtk class hierarchy, generated on-the-fly using a PythonSource and Python's introspection capabilities.
	An example vistrail that creates an interactive treemap can be found here: [http://www.sci.utah.edu/~stevec/classes/cs5630/~~assignment3b~~.vt ~~assignment3b~~.vt].		An example vistrail that creates an interactive treemap can be found here: [http://www.sci.utah.edu/~stevec/classes/cs5630/assignment4b.vt assignment4b.vt].

Stevec at 19:54, 1 December 2007

2007-12-01T19:54:31Z

← Older revision		Revision as of 19:54, 1 December 2007
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	The assignment is due at midnight on December 11th~~. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630"~~.		The assignment is due at midnight on December 11th.
	The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.		The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.

	== Submitting your vistrails ==		== Submitting your vistrails ==
	The assignment is broken into two distinct parts: DTI vis and graph vis. Two different vistrails should be used for these tasks, assignment4a.vt and assignment 4b.vt, respectively. You may start from an empty vistrail or from examples that are given.		The assignment is broken into two distinct parts: DTI vis and graph vis. Two different vistrails should be used for these tasks, assignment4a.vt and assignment 4b.vt, respectively. You may start from an empty vistrail or from examples that are given. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630". Both vistrails will need to be submitted.

	== Assignment 4a: DTI Visualization ==		== Assignment 4a: DTI Visualization ==

Stevec: /* Assignment 4b: Graph Visualization */

2007-12-01T19:51:15Z

Assignment 4b: Graph Visualization

← Older revision		Revision as of 19:51, 1 December 2007
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	== Assignment 4b: Graph Visualization ==		== Assignment 4b: Graph Visualization ==

			The goal of this assignement is to compare several different InfoVis graph layout strategies. InfoVis capabilities in VTK are very new (ie., unstable) and some of the features do not work to well, or crash (I recommend saving often). Thus, this assignment will be somewhat limited in what we can do. The graph we will be visualizing is the vtk class hierarchy, generated on-the-fly using a PythonSource and Python's introspection capabilities.
			An example vistrail that creates an interactive treemap can be found here: [http://www.sci.utah.edu/~stevec/classes/cs5630/assignment3b.vt assignment3b.vt].


			Problem 2a: Replace the tree map with a graph layout (see vtkGraphLayout). Be sure to keep the labels on the resulting trees.


			Problem 2b: Experiment with different graph layout strategies and tag the one you like best. In the notes, comment on why you chose the layout you did. Note: I could not get the vtkTreeLayoutStrategy to work correctly (it always wants to be radial), you may have more or less luck.


			Hints:
			* See the vtk documentation, tests, and examples for the graph layout classes to get the pipelines right.

Stevec: /* Assignment 4a: DTI Visualization */

2007-12-01T18:52:39Z

Assignment 4a: DTI Visualization

← Older revision		Revision as of 18:52, 1 December 2007
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	'''Problem 1c:''' Based on your knowedge of where the highly directional features are, visualize them using several well-placed hyperstreamlines. In the notes for the node, describe how you chose the seed points		'''Problem 1c:''' (Grads Only) Based on your knowedge of where the highly directional features are, visualize them using several well-placed hyperstreamlines. In the notes for the node, describe how you chose the seed points


	'''Problem 1d:''' Create a composite visualization that combines all three techniques described above.		'''Problem 1d:''' Create a composite visualization that combines all three techniques (or two techniques for U-Grads) described above.

Stevec: /* Assignment 4a: DTI Visualization */

2007-12-01T18:51:38Z

Assignment 4a: DTI Visualization

← Older revision		Revision as of 18:51, 1 December 2007
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	== Assignment 4a: DTI Visualization ==		== Assignment 4a: DTI Visualization ==

			The first part of the assignment is to perform some basic visualizations of diffusion tensor data. Because this is the final assignment, it will be a little more difficult because there are no examples given. It also combines many of the techniques covered in other assignments such as color mapping, isosurfacing, glyph visualization, and streamlines.

	This is a diffusion tensor dataset [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbh.vtk gktbh.vtk], and a corresponding anisotropy volume [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbhFA.vtk gktbhFA.vtk]. These volumes cover the right half of a [http://www.cs.utah.edu/~gk Gordon Kindlmann's] brain. They encode information about the structure of the brain matter. The anisotropy volume has high values in regions which are likely white matter in the brain, and these are the regions of interest.		This is a diffusion tensor dataset [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbh.vtk gktbh.vtk], and a corresponding anisotropy volume [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbhFA.vtk gktbhFA.vtk]. These volumes cover the right half of a [http://www.cs.utah.edu/~gk Gordon Kindlmann's] brain. They encode information about the structure of the brain matter. The anisotropy volume has high values in regions which are likely white matter in the brain, and these are the regions of interest.

Stevec: /* Assignment 4a: DTI Visualization */

2007-12-01T18:47:13Z

Assignment 4a: DTI Visualization

← Older revision		Revision as of 18:47, 1 December 2007
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	'''Problem 1d:''' Create a composite visualization that combines all three techniques described above.		'''Problem 1d:''' Create a composite visualization that combines all three techniques described above.


	'''Hints:'''		'''Hints:'''

Stevec: /* Assignment 4a: DTI Visualization */

2007-12-01T18:46:35Z

Assignment 4a: DTI Visualization

← Older revision		Revision as of 18:46, 1 December 2007
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	'''Problem 1d:''' Create a composite visualization that combines all three techniques described above.		'''Problem 1d:''' Create a composite visualization that combines all three techniques described above.

	"Hints:"		'''Hints:'''
	* Multiple isosurfaces can be easily defined using the GenerateValues method.		* Multiple isosurfaces can be easily defined using the GenerateValues method.
	* Combining two disjoint datasets (tensors and scalars) into one dataset requires a vtkMergeFilter.		* Combining two disjoint datasets (tensors and scalars) into one dataset requires a vtkMergeFilter.