BRAINSCut - Revision history

Vmagnotta: /* Figures */

2008-12-10T21:53:32Z

Figures

Vmagnotta at 21:53, 10 December 2008

2008-12-10T21:53:12Z

Vmagnotta at 21:52, 10 December 2008

2008-12-10T21:52:20Z

Vmagnotta at 21:51, 10 December 2008

2008-12-10T21:51:58Z

Vmagnotta at 21:49, 10 December 2008

2008-12-10T21:49:50Z

Vmagnotta at 21:48, 10 December 2008

2008-12-10T21:48:44Z

Vmagnotta at 21:43, 10 December 2008

2008-12-10T21:43:11Z

Vmagnotta at 15:55, 10 December 2008

2008-12-10T15:55:25Z

Vmagnotta at 15:30, 10 December 2008

2008-12-10T15:30:30Z

Vmagnotta at 15:29, 10 December 2008

2008-12-10T15:29:43Z

@@ Line 26: / Line 26: @@
 ===Figures===
-<gallery Caption="BRAINSTracer" widths="300px" heights="300px" perrow="2">
+<gallery Caption="BRAINSCut" widths="300px" heights="300px" perrow="2">
 Image:BRAINS-ANN-Brain-Subject1-T1.png|Brain Mask generated using BRAINSMush image and BRAINSCut overlaid on T1 for Subject 1
 Image:BRAINS-ANN-Brain-Subject1-T2.png|Brain Mask generated using BRAINSMush image and BRAINSCut overlaid on T2 for Subject 1
@@ Line 36: / Line 36: @@
 Image:BRAINS-ANN-Brain-Subject3-T2.png|Brain Mask generated using BRAINSMush image and BRAINSCut overlaid on T2 for Subject 3
 </gallery>
 ===Usage===

@@ Line 2: / Line 2: @@
-'''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: 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.
@@ Line 8: / Line 8: @@
-'''Progress:'''
+===Progress===
 #Integration with a high dimensional registration to the atlas probability map
 #Improved thresholding of the output activation maps
@@ Line 15: / Line 15: @@
-'''To Do:'''
+===To Do===
 #Complete integration with the FANN library
 #Link to a BSD style neural network library
@@ Line 21: / Line 21: @@
-'''Key Investigators:'''
+===Key Investigators===
 * University of Iowa: Hans Johnson, Ronald Pierson, Kent Williams, Greg Harris, Vincent Magnotta
-'''Figures:'''
+===Figures===
 <gallery Caption="BRAINSTracer" widths="300px" heights="300px" perrow="2">
 Image:BRAINS-ANN-Brain-Subject1-T1.png|Brain Mask generated using BRAINSMush image and BRAINSCut overlaid on T1 for Subject 1
@@ Line 39: / Line 39: @@
-'''Usage:'''
+===Usage===
    BRAINSCut  [--processinformationaddress <std::string>] [--xml] [--echo]
                [--applyModel] [--trainModel] [--createVectors]
@@ Line 90: / Line 90: @@
-'''Links:'''
+===Links===
 *[http://www.psychiatry.uiowa.edu University of Iowa Department of Psychiatry]
 *[http://mri.radiology.uiowa.edu University of Iowa MRI Center]
-'''Papers:'''
+===Papers===
 *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.

@@ Line 44: / Line 44: @@
                [--generateProbability] [--trainModelStartIndex <int>]
                [--netConfiguration <std::string>] [--] [--version] [-h]
-−
     Description: Automatic Segmentation using neural networks
 Where:

@@ Line 40: / Line 40: @@
 '''Usage:'''
 '''Links:'''
 *[http://www.psychiatry.uiowa.edu University of Iowa Department of Psychiatry]

@@ Line 16: / Line 16: @@
 '''To Do:'''
-#Complete integeration with the FANN library
+#Complete integration with the FANN library
 #Link to a BSD style neural network library
 #Look at the ability to use for segmentation of cortical regions

← Older revision		Revision as of 15:55, 10 December 2008
Line 1:		Line 1:
		+	Back 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: 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: 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.

← Older revision		Revision as of 15:30, 10 December 2008
Line 6:		Line 6:
	#Integration with a high dimensional registration to the atlas probability map		#Integration with a high dimensional registration to the atlas probability map
	#Improved thresholding of the output activation maps		#Improved thresholding of the output activation maps
		+	#Code added to NITRC

← Older revision		Revision as of 15:29, 10 December 2008
Line 30:		Line 30:

	'''Papers:'''		'''Papers:'''
−	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.