[Blends-commit] r2212 - projects/med/trunk/debian-med/tasks

Debian Pure Blends Subversion Commit noreply at alioth.debian.org
Wed Jun 16 13:29:23 UTC 2010


Author: mhanke-guest
Date: Wed Jun 16 13:29:12 2010
New Revision: 2212
URL: http://svn.debian.org/viewsvn/blends?rev=2212&view=rev

Log:
Cleanup of now official packages.

Modified:
   projects/med/trunk/debian-med/tasks/imaging

Modified: projects/med/trunk/debian-med/tasks/imaging
URL: http://svn.debian.org/viewsvn/blends/projects/med/trunk/debian-med/tasks/imaging?rev=2212&view=diff&r1=2212&r2=2211&p1=projects/med/trunk/debian-med/tasks/imaging&p2=projects/med/trunk/debian-med/tasks/imaging
==============================================================================
--- projects/med/trunk/debian-med/tasks/imaging	(original)
+++ projects/med/trunk/debian-med/tasks/imaging	Wed Jun 16 13:29:12 2010
@@ -668,17 +668,6 @@
 
 
 Depends: mrtrix
-Homepage: http://www.brain.org.au/software/mrtrix
-License: GPL-3
-Language: C++
-Responsible: Michael Hanke <michael.hanke at gmail.com>
-WNPP: 579470
-Pkg-Description: diffusion-weighted MRI white matter tractography
- Set of tools to perform diffusion-weighted MRI white matter tractography of the
- brain in the presence of crossing fibres, using Constrained Spherical
- Deconvolution, and a probabilisitic streamlines algorithm. Magnetic resonance
- images in DICOM, ANALYZE, or uncompressed NIfTI format are supported.
-Pkg-URL: http://neuro.debian.net/pkgs/mrtrix.html
 Published-Title: Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution
 Published-Authors: J-Donald Tournier, Fernando Calamantea, Alan Connelly
 Published-In: NeuroImage, 35: 1459-1472
@@ -687,21 +676,6 @@
 
 
 Depends: ants
-Homepage: http://www.picsl.upenn.edu/ANTS
-License: BSD
-Language: C++
-Responsible: Yaroslav Halchenko <debian at onerussian.com>
-Pkg-URL: http://neuro.debian.net/pkgs/ants.html
-WNPP: 579569
-Pkg-Description: advanced normalization tools for brain and image mapping
- The ANTs package is designed to enable researchers with advanced tools for
- brain and image mapping. Many of the ANTs registration tools are
- diffeomorphic, but deformation (elastic and BSpline) transformations are
- available. Unique components of ANTs include multivariate similarity metrics,
- landmark guidance, the ability to use label images to guide the mapping and
- both greedy and space-time optimal implementations of diffeomorphisms. The
- symmetric normalization (SyN) strategy is a part of the ANTs toolkit as is
- directly manipulated free form deformation (DMFFD).
 Published-Title: The optimal template effect in hippocampus studies of diseased populations
 Published-Authors: Brian B. Avants, Paul Yushkevich, John Pluta, David Minkoff, Marc Korczykowski, John Detre and James C. Gee
 Published-In: NeuroImage, 49: 2457-2466
@@ -711,24 +685,6 @@
 
 
 Depends: itksnap
-Homepage: http://www.itksnap.org
-License: GPL-3
-Language: C++
-Responsible: Michael Hanke <michael.hanke at gmail.com>
-WNPP: 579588
-Pkg-URL: http://neuro.debian.net/pkgs/itksnap.html
-Pkg-Description: semi-automatic segmentation of structures in 3D images
- SNAP provides semi-automatic segmentation of structures in medical
- images (e.g.  magnetic resonance images of the brain) using active
- contour methods, as well as manual delineation and image navigation.
- Noteworthy features are:
- .
-  * Linked cursor for seamless 3D navigation
-  * Manual segmentation in three orthogonal planes at once
-  * Support for many different 3D image formats, including NIfTI
-  * Support for concurrent, linked viewing and segmentation of multiple images
-  * Limited support for color images (e.g., diffusion tensor maps)
-  * 3D cut-plane tool for fast post-processing of segmentation results
 Published-Title: User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability
 Published-Authors: Paul A. Yushkevich, Joseph Piven, Heather Cody Hazlett, Rachel Gimpel Smith, Sean Ho, James C. Gee, and Guido Gerig
 Published-In: Neuroimage, 31: 1116-1128



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