Difference between revisions of "3D SIFT VIEW"
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Image:3D_SIFT_BRAIN.png|Brain MR, 2D slice visualization | Image:3D_SIFT_BRAIN.png|Brain MR, 2D slice visualization | ||
</gallery> | </gallery> | ||
| + | |||
| + | ==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 | + | * 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== | ==Project Description== | ||
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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
Lung CT, 3D volume visualization
Brain MR, 2D slice visualization
New Visualization
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
