Difference between revisions of "2014 Summer Project Week:Tumor Heterogeneity Analysis"
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*Create a Slicer module to analyze a segmented tumor and its parameters maps (i.e. k-trans values from DCE-MRI). | *Create a Slicer module to analyze a segmented tumor and its parameters maps (i.e. k-trans values from DCE-MRI). | ||
*Implement known metrics to extract feature data | *Implement known metrics to extract feature data | ||
| − | *Draft a framework to export, visualize, and compare information among cases | + | *Draft a framework to export, visualize, and compare information among cases |
</div> | </div> | ||
<div style="width: 27%; float: left; padding-right: 3%;"> | <div style="width: 27%; float: left; padding-right: 3%;"> | ||
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*Design a Slicer module using python and numpy | *Design a Slicer module using python and numpy | ||
*Research and implement various classes of metrics and features: i.e., first-order statistics, morphology/shape, fractal dimensions, geometrical measures, texture-based features | *Research and implement various classes of metrics and features: i.e., first-order statistics, morphology/shape, fractal dimensions, geometrical measures, texture-based features | ||
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</div> | </div> | ||
<div style="width: 27%; float: left; padding-right: 3%;"> | <div style="width: 27%; float: left; padding-right: 3%;"> | ||
<h3>Progress</h3> | <h3>Progress</h3> | ||
*Implementing geometric measures and features derived from texture matrices, while researching new metrics. | *Implementing geometric measures and features derived from texture matrices, while researching new metrics. | ||
| + | </div> | ||
| + | <div style="width: 27%; float: left; padding-right: 3%;"> | ||
| + | <h3>References</h3> | ||
| + | *https://www.slicer.org/wiki/Documentation/Nightly/Extensions/OpenCAD | ||
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Latest revision as of 17:25, 10 July 2017
Home < 2014 Summer Project Week:Tumor Heterogeneity Analysis
Key Investigators
- Vivek Narayan
- Jayender Jagadeesan
Project Description
HeterogeneityCAD module for Slicer (openCAD Extension): Quantify the heterogeneity of Breast tumors and their parameter maps through several classes of metrics.
Objective
- Create a Slicer module to analyze a segmented tumor and its parameters maps (i.e. k-trans values from DCE-MRI).
- Implement known metrics to extract feature data
- Draft a framework to export, visualize, and compare information among cases
Approach, Plan
- Design a Slicer module using python and numpy
- Research and implement various classes of metrics and features: i.e., first-order statistics, morphology/shape, fractal dimensions, geometrical measures, texture-based features
Progress
- Implementing geometric measures and features derived from texture matrices, while researching new metrics.
