Difference between revisions of "BRAINSCut"
From NAMIC Wiki
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'''Summary:''' | '''Summary:''' | ||
| − | BRAINSCut is a software package for segmentation of structures using artificial neural networks. Currently this tool supports the segmentation of the following structures: caudate, putamen, thalamus, hippocampus, anterior cerebellum, interior posterior cerebellum, superior posterior cerebellum, corpus medullary. Future regions will include the globus pallidus, amygdala, and nucleus accumbens. The command line uses the Slicer3 execution model framework. | + | |
| + | BRAINSCut is a software package for segmentation of structures using artificial neural networks. Currently this tool supports the segmentation of the following structures: brain, caudate, putamen, thalamus, hippocampus, anterior cerebellum, interior posterior cerebellum, superior posterior cerebellum, corpus medullary. Future regions will include the globus pallidus, amygdala, and nucleus accumbens. The command line uses the Slicer3 execution model framework. | ||
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#Improved thresholding of the output activation maps | #Improved thresholding of the output activation maps | ||
#Code added to NITRC | #Code added to NITRC | ||
| + | #Coupled Neural network with MUSH Brain to generate a brain mask without requiring tissue classification | ||
'''To Do:''' | '''To Do:''' | ||
| − | #Link to a BSD style | + | #Complete integeration with the FANN library |
| + | #Link to a BSD style neural network library | ||
#Look at the ability to use for segmentation of cortical regions | #Look at the ability to use for segmentation of cortical regions | ||
Revision as of 21:43, 10 December 2008
Home < BRAINSCutBack to NA-MIC Brains Collaboration
Summary:
BRAINSCut is a software package for segmentation of structures using artificial neural networks. Currently this tool supports the segmentation of the following structures: brain, caudate, putamen, thalamus, hippocampus, anterior cerebellum, interior posterior cerebellum, superior posterior cerebellum, corpus medullary. Future regions will include the globus pallidus, amygdala, and nucleus accumbens. The command line uses the Slicer3 execution model framework.
Progress:
- Integration with a high dimensional registration to the atlas probability map
- Improved thresholding of the output activation maps
- Code added to NITRC
- Coupled Neural network with MUSH Brain to generate a brain mask without requiring tissue classification
To Do:
- Complete integeration with the FANN library
- Link to a BSD style neural network library
- Look at the ability to use for segmentation of cortical regions
Key Investigators:
- University of Iowa: Hans Johnson, Ronald Pierson, Kent Williams, Greg Harris, Vincent Magnotta
Figures:
Usage:
Links:
Papers:
- Powell S, Magnotta VA, Johnson H, Jammalamadaka VK, Pierson R, Andreasen NC. Registration and machine learning-based automated segmentation of subcortical and cerebellar brain structures. Neuroimage. 39(1):238-47, 2008.
- Magnotta VA, Heckel D, Andreasen NC, Cizadlo T, Corson PW, Ehrhardt JC, Yuh WT. Measurement of brain structures with artificial neural networks: two- and three-dimensional applications. Radiology. 211(3):781-90, 1999.
