Difference between revisions of "3D SIFT VIEW"

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<gallery>
 
<gallery>
 
Image:PW-2015SLC.png|[[2015_Winter_Project_Week#Projects|Projects List]]
 
Image:PW-2015SLC.png|[[2015_Winter_Project_Week#Projects|Projects List]]
Image:slicer_lung_features.png
+
Image:slicer_lung_features.png|Lung CT, 3D volume visualization
Image:3D_SIFT_BRAIN.png
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Image:3D_SIFT_BRAIN.png|Brain MR, 2D slice visualization
 
</gallery>
 
</gallery>
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==New Visualization==
 +
[[File:3D_SIFT_Lung.png|500px|thumb|left|Lung CT]]
 +
[[File:3D_SIFT_Prostate.png|300px|thumb|left|Prostate US]]
  
 
==Key Investigators==
 
==Key Investigators==
* Matthew Toews BWH
+
* Matthew Toews, Raul San Jose, Steve Pieper, Nicole Aucoin, Bill Lorensen, Lauren O'Donnell, Andriy Fedorov, William Wells BWH
* Raul San Jose BWH
+
 
* Steve Pieper BWH
+
==Code==
* Nicole Aucoin BWH
+
3D SIFT feature extraction code http://www.matthewtoews.com/fba/featExtract1.5.zip
* Andriy Fedorov, BWH
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* William Wells BWH
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Python conversion code [[Media:3D_SIFT_VISUALIZATION.gz]]
  
 
==Project Description==
 
==Project Description==
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<h3>Approach, Plan</h3>
 
<h3>Approach, Plan</h3>
 
* Investigate methods for visualizing 3D feature location, scale, orientation and group label (e.g. diseased, healthy)
 
* Investigate methods for visualizing 3D feature location, scale, orientation and group label (e.g. diseased, healthy)
 +
* Location, scale: spheres (markups), group labels: color/transparency
 
* Visualization: Slicer Python module based on Slicer Markups
 
* Visualization: Slicer Python module based on Slicer Markups
 
* Data preparation: c++
 
* Data preparation: c++
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<div style="width: 27%; float: left; padding-right: 3%;">
 
<div style="width: 27%; float: left; padding-right: 3%;">
 
<h3>Progress</h3>
 
<h3>Progress</h3>
*
+
* Evaluated Slicer fiducials and VTK glyph models for feature display
 +
* Developed a python script to convert a 3D SIFT feature file into a VTK model (thanks Lauren, Nicole)
 +
* ToDo:
 +
** display feature orientation (possibly as another glyph)
 +
** display varying feature opacity
 
</div>
 
</div>
 
</div>
 
</div>

Latest revision as of 16:45, 9 January 2015

Home < 3D SIFT VIEW

New Visualization

Lung CT
Prostate US

Key Investigators

  • Matthew Toews, Raul San Jose, Steve Pieper, Nicole Aucoin, Bill Lorensen, Lauren O'Donnell, Andriy Fedorov, William Wells BWH

Code

3D SIFT feature extraction code http://www.matthewtoews.com/fba/featExtract1.5.zip

Python conversion code Media:3D_SIFT_VISUALIZATION.gz

Project Description

Objective

  • Generate effective visualizations for 3D SIFT feature sets in Slicer.

Approach, Plan

  • Investigate methods for visualizing 3D feature location, scale, orientation and group label (e.g. diseased, healthy)
  • Location, scale: spheres (markups), group labels: color/transparency
  • Visualization: Slicer Python module based on Slicer Markups
  • Data preparation: c++

Progress

  • Evaluated Slicer fiducials and VTK glyph models for feature display
  • Developed a python script to convert a 3D SIFT feature file into a VTK model (thanks Lauren, Nicole)
  • ToDo:
    • display feature orientation (possibly as another glyph)
    • display varying feature opacity