multithreaded 64-bit matlab Search Results


matlab 2009a  (MathWorks Inc)
90
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Matlab 2009a, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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multithreaded c mex files  (MathWorks Inc)
90
MathWorks Inc multithreaded c mex files
Multithreaded C Mex Files, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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matlab r2015b  (MathWorks Inc)
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MathWorks Inc matlab r2015b
Matlab R2015b, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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spm2 software  (MathWorks Inc)
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MathWorks Inc spm2 software
The enantiomorphic normalization algorithm. A structural image and a matching lesion mask are aligned in the sagittal midline using rigid body coregistration to the opto-isometrically flipped version of the structural image. The mask is then flipped opto-isometrically and used to extract the signal within the precise region in the unaffected hemisphere that corresponds to the lesion on the other side. This is then used to replace the signal corresponding to the lesion. The resultant corrected image is then normalized using <t>SPM2's</t> standard spatial normalization routine.
Spm2 Software, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


The enantiomorphic normalization algorithm. A structural image and a matching lesion mask are aligned in the sagittal midline using rigid body coregistration to the opto-isometrically flipped version of the structural image. The mask is then flipped opto-isometrically and used to extract the signal within the precise region in the unaffected hemisphere that corresponds to the lesion on the other side. This is then used to replace the signal corresponding to the lesion. The resultant corrected image is then normalized using SPM2's standard spatial normalization routine.

Journal: Neuroimage

Article Title: Enantiomorphic normalization of focally lesioned brains

doi: 10.1016/j.neuroimage.2007.10.002

Figure Lengend Snippet: The enantiomorphic normalization algorithm. A structural image and a matching lesion mask are aligned in the sagittal midline using rigid body coregistration to the opto-isometrically flipped version of the structural image. The mask is then flipped opto-isometrically and used to extract the signal within the precise region in the unaffected hemisphere that corresponds to the lesion on the other side. This is then used to replace the signal corresponding to the lesion. The resultant corrected image is then normalized using SPM2's standard spatial normalization routine.

Article Snippet: All other procedures were implemented in SPM2 ( http://www.fil.ion.ucl.ac.uk/spm/ ) run under MATLAB 7.2 64 bit for Linux with a multithreaded, Opteron-tuned, custom BLAS by Kazushige Goto ( http://www.tacc.utexas.edu/~kgoto/ ) on a four-core 2.6-GHz AMD Opteron custom-built machine.

Techniques:

Mean SPM(t) map of the contrast between cost function masking and the enantiomorphic methods (T2 dataset with zero-filled lesions). The displacement fields for each subject (305 scans per condition) were log transformed and entered into a one-way ANCOVA with log lesion size as a covariate. Only fields derived from cost function masking and the enantiomorphic method were included in the analysis. In all subjects all voxels within the brain survived a p < 0.05 family-wise error corrected threshold, showing that the enantiomorphic method is superior across all voxels. The figure shows the mean t value across subjects. The figure was generated using the slice_overlay tool for SPM2 written by Matthew Brett ( http://imaging.mrc-cbu.cam.ac.uk/imaging/DisplaySlices ).

Journal: Neuroimage

Article Title: Enantiomorphic normalization of focally lesioned brains

doi: 10.1016/j.neuroimage.2007.10.002

Figure Lengend Snippet: Mean SPM(t) map of the contrast between cost function masking and the enantiomorphic methods (T2 dataset with zero-filled lesions). The displacement fields for each subject (305 scans per condition) were log transformed and entered into a one-way ANCOVA with log lesion size as a covariate. Only fields derived from cost function masking and the enantiomorphic method were included in the analysis. In all subjects all voxels within the brain survived a p < 0.05 family-wise error corrected threshold, showing that the enantiomorphic method is superior across all voxels. The figure shows the mean t value across subjects. The figure was generated using the slice_overlay tool for SPM2 written by Matthew Brett ( http://imaging.mrc-cbu.cam.ac.uk/imaging/DisplaySlices ).

Article Snippet: All other procedures were implemented in SPM2 ( http://www.fil.ion.ucl.ac.uk/spm/ ) run under MATLAB 7.2 64 bit for Linux with a multithreaded, Opteron-tuned, custom BLAS by Kazushige Goto ( http://www.tacc.utexas.edu/~kgoto/ ) on a four-core 2.6-GHz AMD Opteron custom-built machine.

Techniques: Transformation Assay, Derivative Assay, Generated, Imaging