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Python in NeuroImaging
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======================
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-
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Please provide for every sub-project a brief Description, list of
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Features, some nice figure if you have any. Hopefully eventually we
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get enough of tasty materials someone could compose into a flier.
@@ -30,13 +29,41 @@ NiBabel
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~~~~~~~
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http://nipy.org/nibabel
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+ .. figure :: ../pics/reggie.png
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+ :alt: nibabel
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+ :align: right
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+ :figwidth: 35%
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+
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+ Nibabel provides read and write access to some common medical and neuroimaging
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+ file formats, including: ANALYZE _ (plain, SPM99, SPM2), GIFTI _, NIfTI1 _, MINC _,
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+ as well as PAR/REC. NiBabel is the successor of PyNIfTI _.
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+
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+ .. _ANALYZE : http://www.grahamwideman.com/gw/brain/analyze/formatdoc.htm
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+ .. _NIfTI1 : http://nifti.nimh.nih.gov/nifti-1/
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+ .. _MINC : http://wiki.bic.mni.mcgill.ca/index.php/MINC
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+ .. _PyNIfTI : http://niftilib.sourceforge.net/pynifti/
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+ .. _GIFTI : http://www.nitrc.org/projects/gifti
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+
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+ The various image format classes give full or selective access to header (meta)
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+ information and access to the image data is made available via NumPy arrays.
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+
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Analysis
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--------
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NiPy
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~~~~
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http://nipy.org/nipy
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+ NIPY has algorithms for the analysis of neuroimaging data including:
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+
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+ * General linear model statistical analysis
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+ * Combined slice time correction and motion correction
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+ * General image registration routines with flexible cost functions, optimizers
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+ and resampling schemes
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+ * Image segmentation
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+ * Basic visualization of results in 2D and 3D
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+ * Basic time series diagnostics
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+ * Clustering and activation pattern analysis across subjects
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NiPype
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~~~~~~
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~~~~
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http://nipy.org/dipy
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+ .. figure :: ../pics/dipy-banner.png
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+ :alt: nibabel
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+ :align: right
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+ :figwidth: 35%
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+
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+ Dipy is an international, free and open soure software project for
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+ diffusion magnetic resonance imaging analysis.
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+ Dipy is multiplatform and will run under any standard operating system such as
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+ *Windows *, *Linux *, *Mac OS X *.
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+ Just some of our **state-of-the-art ** applications are:
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+ - Reconstruction algorithms e.g. GQI, DTI
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+ - Tractography generation algorithms e.g. EuDX
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+ - Intelligent downsampling of tracks
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+ - Ultra fast tractography clustering
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+ - Resampling datasets with anisotropic voxels to isotropic
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+ - Visualizing multiple brains simultaneously
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+ - Finding track correspondence between different brains
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+ - Warping tractographies into another space e.g. MNI space
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+ - Reading many different file formats e.g. Trackvis or Nifti
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+ - Dealing with huge tractographies without memory restrictions
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+ - Playing with datasets interactively without storing
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+ - And much more and even more to come in next releases
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+
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NiTime
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~~~~~~
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