Difference between revisions of "2014 Project Week:GrowCutLevelSetLA"
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Image:PW-SLC2014.png|[[2014_Winter_Project_Week#Projects|Projects List]] | Image:PW-SLC2014.png|[[2014_Winter_Project_Week#Projects|Projects List]] | ||
| + | Image:AFib_GrowCut.png | ||
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<div style="width: 27%; float: left; padding-right: 3%;"> | <div style="width: 27%; float: left; padding-right: 3%;"> | ||
<h3>Objective</h3> | <h3>Objective</h3> | ||
| − | * | + | * We have created an editor extension for quickly initializing, interactively segmenting targets. We will improve this module for the LA segmentation. |
| + | |||
</div> | </div> | ||
<div style="width: 27%; float: left; padding-right: 3%;"> | <div style="width: 27%; float: left; padding-right: 3%;"> | ||
<h3>Approach, Plan</h3> | <h3>Approach, Plan</h3> | ||
| − | * | + | * Create a loadable module from an existing command line module |
| + | * Discuss with Josh about similar work. CARMA has also worked on this using Graph Cuts method. | ||
</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> | ||
| − | * | + | * Demoed and discussed with collaborators and start improving it based on these feedbacks |
| + | * Working on its extension to support multi-label segmentation | ||
</div> | </div> | ||
</div> | </div> | ||
| + | |||
| + | == References == | ||
| + | * [http://www.na-mic.org/Wiki/index.php/DBP3:Utah Utah DBP] | ||
Latest revision as of 16:33, 10 January 2014
Home < 2014 Project Week:GrowCutLevelSetLA
Key Investigators
- Liangjia Zhu, Ivan Kolesov, Allen Tannenbaum, Stony Brook University
- Yi Gao, University of Alabama Birmingham
Objective
- We have created an editor extension for quickly initializing, interactively segmenting targets. We will improve this module for the LA segmentation.
Approach, Plan
- Create a loadable module from an existing command line module
- Discuss with Josh about similar work. CARMA has also worked on this using Graph Cuts method.
Progress
- Demoed and discussed with collaborators and start improving it based on these feedbacks
- Working on its extension to support multi-label segmentation
