Difference between revisions of "2009 UNC HAMMER WML"
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| + | |[[Image:NAMIC-SLC.jpg|thumb|320px|Return to [[2009_Winter_Project_Week|Project Week Main Page]] ]] | ||
| + | |[[Image:HammerABrain.png|thumb|320px|Deformable registration using HAMMER ('''H'''eirarchical '''A'''ttribute '''M'''atching '''M'''echanism for '''E'''lastic '''R'''egistration)]] | ||
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===Key Investigators=== | ===Key Investigators=== | ||
* UNC: Dinggang Shen | * UNC: Dinggang Shen | ||
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<div style="width: 40%; float: left; padding-right: 3%;"> | <div style="width: 40%; float: left; padding-right: 3%;"> | ||
<h1>Objective</h1> | <h1>Objective</h1> | ||
| − | + | Design ITK classes for Hierarchical Attribute Matching Mechanism for Elastic Registration (HAMMER) and White Matter Lesion segmentation so that these algorithms can be easily implemented using the Insight Toolkit and integrated into Slicer. The goals of the week is to analyze the algorithms on the object level, map components to existing ITK classes, identify gaps, and start implementation. Will also identify testing dataset and generate ground truth for future test. | |
</div> | </div> | ||
<div style="width: 27%; float: left; padding-right: 3%;"> | <div style="width: 27%; float: left; padding-right: 3%;"> | ||
<h1>Approach, Plan</h1> | <h1>Approach, Plan</h1> | ||
| − | Software process embraced by NA-MIC community. | + | Software process embraced by NA-MIC community. |
</div> | </div> | ||
<div style="width: 27%; float: left;"> | <div style="width: 27%; float: left;"> | ||
<h1>Progress</h1> | <h1>Progress</h1> | ||
| − | + | Both HAMMER and WML segmentation algorithms have been distributed in binary forms for a number of years and have been used by some research groups. We will start with the algorithms in their current forms to generate ground truth on publically available datasets. | |
</div> | </div> | ||
<br style="clear: both;" /> | <br style="clear: both;" /> | ||
</div> | </div> | ||
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| + | ==References== | ||
| + | * Dinggang Shen, Christos Davatzikos, [http://www.med.unc.edu/~dgshen/papers/Hammer_VersionInTMI.pdf HAMMER: Hierarchical Attribute Matching Mechanism for Elastic Registration], IEEE Trans. on Medical Imaging, 21(11):1421-1439, Nov 2002. | ||
| + | |||
| + | * Zhiqiang Lao, Dinggang Shen, Dengfeng Liu, Abbas F Jawad, Elias R Melhem, Lenore J Launer, Nick R Bryan, Christos Davatzikos, [http://www.med.unc.edu/~dgshen/papers/WMlesionSegmentation.pdf Computer-Assisted Segmentation of White Matter Lesions in 3D MR images, Using Pattern Recognition], Academic Radiology, 15(3):300-313, March 2008. | ||
Revision as of 21:04, 22 December 2008
Home < 2009 UNC HAMMER WML Return to Project Week Main Page |
Key Investigators
- UNC: Dinggang Shen
- GE Research: Xiaodong Tao, Jim Miller
Objective
Design ITK classes for Hierarchical Attribute Matching Mechanism for Elastic Registration (HAMMER) and White Matter Lesion segmentation so that these algorithms can be easily implemented using the Insight Toolkit and integrated into Slicer. The goals of the week is to analyze the algorithms on the object level, map components to existing ITK classes, identify gaps, and start implementation. Will also identify testing dataset and generate ground truth for future test.
Approach, Plan
Software process embraced by NA-MIC community.
Progress
Both HAMMER and WML segmentation algorithms have been distributed in binary forms for a number of years and have been used by some research groups. We will start with the algorithms in their current forms to generate ground truth on publically available datasets.
References
- Dinggang Shen, Christos Davatzikos, HAMMER: Hierarchical Attribute Matching Mechanism for Elastic Registration, IEEE Trans. on Medical Imaging, 21(11):1421-1439, Nov 2002.
- Zhiqiang Lao, Dinggang Shen, Dengfeng Liu, Abbas F Jawad, Elias R Melhem, Lenore J Launer, Nick R Bryan, Christos Davatzikos, Computer-Assisted Segmentation of White Matter Lesions in 3D MR images, Using Pattern Recognition, Academic Radiology, 15(3):300-313, March 2008.
