Difference between revisions of "BRAINSCut"
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(New page: 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...) |
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| − | Powell S, Magnotta VA, Johnson H, Jammalamadaka VK, Pierson R, Andreasen NC. [http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6WNP-4PGGP30-3&_user=440026&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000020939&_version=1&_urlVersion=0&_userid=440026&md5=c783cac6caa49b7253ab0d08c9da068b Registration and machine learning-based automated segmentation of subcortical and cerebellar brain structures]. Neuroimage. 39(1):238-47, 2008. | + | *Powell S, Magnotta VA, Johnson H, Jammalamadaka VK, Pierson R, Andreasen NC. [http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6WNP-4PGGP30-3&_user=440026&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000020939&_version=1&_urlVersion=0&_userid=440026&md5=c783cac6caa49b7253ab0d08c9da068b 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. [http://radiology.rsnajnls.org/cgi/content/full/211/3/781 Measurement of brain structures with artificial neural networks: two- and three-dimensional applications]. Radiology. 211(3):781-90, 1999. | ||
Revision as of 15:29, 10 December 2008
Home < BRAINSCutBRAINSCut 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.
Progress:
- Integration with a high dimensional registration to the atlas probability map
- Improved thresholding of the output activation maps
To Do:
- 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.
