Package: afni Version: 0.20100917~dfsg.1-1~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 24736 Depends: afni-common (= 0.20100917~dfsg.1-1~squeeze.nd1), tcsh, gifsicle, libjpeg-progs, freeglut3, lesstif2 (>= 1:0.94.4), libc6 (>= 2.7), libf2c2, libgiftiio0, libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libglw1-mesa | libglw1, libgomp1 (>= 4.2.1), libgsl0ldbl (>= 1.9), libgts-0.7-5 (>= 0.7.6), libice6 (>= 1:1.0.0), libnetcdf6, libnifti2, libsm6, libvolpack1, libx11-6, libxext6, libxi6, libxmu6, libxt6 Recommends: nifti-bin, bzip2, ffmpeg Homepage: http://afni.nimh.nih.gov Priority: extra Section: science Filename: pool/main/a/afni/afni_0.20100917~dfsg.1-1~squeeze.nd1_i386.deb Size: 9707272 SHA256: 6e684a5c31237b236eba216c7dde35017e217939bd4d30d515374c4285997f8f SHA1: 9c1262178748faa2e91d77b0a322c278a96a27ae MD5sum: 456f0f1e700fa9668ef15908348d58b6 Description: toolkit for analyzing and visualizing functional MRI data AFNI is an environment for processing and displaying functional MRI data. It provides a complete analysis toolchain, including 3D cortical surface models, and mapping of volumetric data (SUMA). . In addition to its own format AFNI understands the NIfTI format and is therefore easily usable in combination with FSL and Freesurfer. Package: afni-common Source: afni Version: 0.20100917~dfsg.1-1~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 6544 Depends: python, tcsh Homepage: http://afni.nimh.nih.gov Priority: extra Section: science Filename: pool/main/a/afni/afni-common_0.20100917~dfsg.1-1~squeeze.nd1_all.deb Size: 3960850 SHA256: bddd270afdcb6d71e274297dab9a0d46e8e5365a7d0a507727276e32adebb25f SHA1: 851407a589e0c2e457126115b69d0b8670599860 MD5sum: 745ed8f101ee3259de3aeac96bc9087a Description: miscellaneous scripts and data files for AFNI This package provides the required architecture independent parts of AFNI. Package: afni-dev Source: afni Version: 0.20100917~dfsg.1-1~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 10936 Homepage: http://afni.nimh.nih.gov Priority: extra Section: science Filename: pool/main/a/afni/afni-dev_0.20100917~dfsg.1-1~squeeze.nd1_i386.deb Size: 3445760 SHA256: b862889798dab5dbcd2444a3bed81aa8e23cf465f44fafa3886817738e25211b SHA1: 77f65c55b627bc234bfb039af02807f3522b9d87 MD5sum: 660d909c3d788dafdf61bf7e49681934 Description: header and static libraries for AFNI plugin development AFNI is an environment for processing and displaying functional MRI data. It provides a complete analysis toolchain, including 3D cortical surface models, and mapping of volumetric data (SUMA). . This package provides the necessary libraries and header files for AFNI plugin development. Package: ants Version: 1.9+svn532-4~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 36236 Depends: libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libinsighttoolkit3.18, libstdc++6 (>= 4.4.0) Suggests: fsl, gridengine-client Homepage: http://www.picsl.upenn.edu/ANTS/ Priority: extra Section: science Filename: pool/main/a/ants/ants_1.9+svn532-4~squeeze.nd1_i386.deb Size: 11265042 SHA256: 1c4f28e2cdcc0120d6c91ea8c840eb1c480305e4b7b0101aedd546a05c9da6ef SHA1: 1ba5c9fb9fbb905d6a88cbf4bde50fd8737a18d5 MD5sum: 82f8156a3cbdd337b1affe1348aa320a Description: advanced normalization tools for brain and image analysis Advanced Normalization Tools (ANTS) is an ITK-based suite of normalization, segmentation and template-building tools for quantitative morphometric analysis. 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). Package: arno-iptables-firewall Version: 1.9.2.k-3~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 844 Depends: iptables (>= 1.2.11), gawk, debconf (>= 1.3.22) | cdebconf (>= 0.43), debconf (>= 0.5) | debconf-2.0, iproute Recommends: lynx, dnsutils Homepage: http://rocky.eld.leidenuniv.nl/ Priority: optional Section: net Filename: pool/main/a/arno-iptables-firewall/arno-iptables-firewall_1.9.2.k-3~squeeze.nd1_all.deb Size: 132476 SHA256: b002efbc460e228ef300147169187793cc9cc8b36e7acf807567d35aa8d56099 SHA1: 7945add5a3b0968d8deeac27bb6d5bdf667ff03a MD5sum: ebcb9a6d4f275258f76616360ff739d0 Description: single- and multi-homed firewall script with DSL/ADSL support Unlike other lean iptables frontends in Debian, arno-iptables-firewall will setup and load a secure, restrictive firewall by just asking a few question. This includes configuring internal networks for internet access via NAT and potential network services (e.g. http or ssh). . However, it is in no way restricted to this simple setup. Some catch words of additional features, that can be enabled in the well documented configuration file are: DSL/ADSL, Port forwarding, DMZ's, portscan detection, MAC address filtering. Package: biosig-tools Source: biosig4c++ Version: 0.94.1+svn2521-1~pre0~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 628 Depends: libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/biosig-tools_0.94.1+svn2521-1~pre0~squeeze.nd1_i386.deb Size: 243082 SHA256: eb26f94f11c3bfc80450bf66a41a7037c24890c9a1b1077b41c05c0512414e6a SHA1: 50b741afd12c6e68fd068c46cf09a88b12d2aa76 MD5sum: 5a1a5106441320de5c5942222c0b49d1 Description: format conversion tools for biomedical data formats Based on libbiosig4c++ library, this package provides command line tools, such as * save2gdf: converter between different file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDF, BDF, CWFB. save2gdf can be also used to upload or retrieve data from a bscs server. TODO... Extend? ship client/server? Package: caret Version: 5.6.1.3~dfsg.1-1~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 18192 Depends: libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libminc2-1, libqt4-assistant (>= 4:4.5.3), libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.5.3), libqtgui4 (>= 4:4.5.3), libqwt5-qt4, libstdc++6 (>= 4.4.0), libvtk5.2, zlib1g (>= 1:1.2.3.3.dfsg) Suggests: caret-data (>= 5.6~dfsg.1) Homepage: http://brainvis.wustl.edu/wiki/index.php/Caret:About Priority: optional Section: science Filename: pool/main/c/caret/caret_5.6.1.3~dfsg.1-1~squeeze.nd1_i386.deb Size: 7062810 SHA256: 5c6eb8a5b94acb47fef751be2f530737c49e4cddab76de843482fbec14d5e125 SHA1: e08e60b8445a852ae26404a6768c9834c6fec05e MD5sum: 0a24866e67ba186f732773fbad6287c5 Description: Computerized Anatomical Reconstruction and Editing Toolkit This software allows for creating, viewing and manipulating surface reconstructions of the cerebral and cerebellar cortex, viewing volumes and for displaying experimental data on the surfaces and volumes. While Caret is primarily a GUI application with 'caret_command' there is also a versatile command line tool, that allows access to a substantial proportion of Caret's functionality. . Caret can download and use stereotaxic atlases (human, monkey, mouse and rat) from an open online database. . Reference: . Van Essen, D.C., Dickson, J., Harwell, J., Hanlon, D., Anderson, C.H. and Drury, H.A. 2001. An Integrated Software System for Surface-based Analyses of Cerebral Cortex. Journal of American Medical Informatics Association, 8(5), 443-459. Package: caret-data Version: 5.6~dfsg.1-1 Architecture: all Maintainer: Michael Hanke Installed-Size: 236780 Homepage: http://brainmap.wustl.edu/caret Priority: optional Section: science Filename: pool/main/c/caret-data/caret-data_5.6~dfsg.1-1_all.deb Size: 175205418 SHA256: 329a14cfd5547064496d4f6909db62578412857ad7d5f73e129335481f550b47 SHA1: 7d6cbdd77b04f258327d2bc9fcc4b0494fcf71bc MD5sum: e5f41497554088124975dfc27ba6378b Description: common data files for Caret This package provides online help, tutorials and atlas datasets for Caret. Package: dicomnifti Version: 2.28.14-2~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 476 Depends: libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libnifti2, libstdc++6 (>= 4.4.0) Homepage: http://cbi.nyu.edu/software/dinifti.php Priority: optional Section: science Filename: pool/main/d/dicomnifti/dicomnifti_2.28.14-2~squeeze.nd1_i386.deb Size: 146588 SHA256: 28fa96633deeb30dff4a871cae75b831684ac8a6e0bbb5e8dacdfa3f964980d2 SHA1: bf3815e66ca5afc2be8169706ced47978c021215 MD5sum: e13e3ee31ea0cab9865af7a1202cd871 Description: converts DICOM files into the NIfTI format The dinifti program converts MRI images stored in DICOM format to NIfTI format. The NIfTI format is thought to be the new standard image format for medical imaging and can be used with for example with FSL, AFNI, SPM, Caret or Freesurfer. . dinifti converts single files, but also supports fully automatic batch conversions of complete dicomdirs. Additionally, converted NIfTI files can be properly named, using image series information from the DICOM files. Package: fslview Version: 3.1.8+4.1.6-2~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 3864 Depends: libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libnewmat10ldbl, libnifti2, libqt3-mt (>= 3:3.3.8b), libqwt4c2, libstdc++6 (>= 4.4.0), libvtk5.4, libvtk5.4-qt3 Recommends: fslview-doc Suggests: fsl-atlases Conflicts: fsl-fslview Replaces: fsl-fslview Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: science Filename: pool/main/f/fslview/fslview_3.1.8+4.1.6-2~squeeze.nd1_i386.deb Size: 1493774 SHA256: a124d69a68e3c33e3d872896150655898e2e0c7c6045117e18f8130fc126f4c2 SHA1: 38bea305cfeb6ff7b7cc9819573f0ded042b95e2 MD5sum: 559f71c004dce3aa4773767a5defa231 Description: viewer for (f)MRI and DTI data This package provides a viewer for 3d and 4d MRI data as well as DTI images. FSLView is able to display ANALYZE and NIFTI files. The viewer supports multiple 2d viewing modes (orthogonal, lightbox or single slices), but also 3d volume rendering. Additionally FSLView is able to visualize timeseries and can overlay metrical and stereotaxic atlas data. . FSLView is part of FSL. Package: fslview-doc Source: fslview Version: 3.1.8+4.1.6-2~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3216 Depends: qt3-assistant Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_3.1.8+4.1.6-2~squeeze.nd1_all.deb Size: 2378936 SHA256: a8fbd782cbb61ed77104e5e28da08040c63de551af6dda1e6ee41a098b40dcc7 SHA1: 565f0f4026969f9fa84091efdec611106608ebf8 MD5sum: f3f752fb3534ec465e7f6c98503ec376 Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: gifti-bin Source: gifticlib Version: 1.0.9-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 124 Depends: libc6 (>= 2.1), libexpat1 (>= 1.95.8), libgiftiio0, libnifti2, zlib1g (>= 1:1.1.4) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: utils Filename: pool/main/g/gifticlib/gifti-bin_1.0.9-1~squeeze.nd1_i386.deb Size: 28730 SHA256: d39ded92265112712c77d9117b70fa915b56f1cc3681e498c155754ad64cdc58 SHA1: 410001a3b15e8fd43a44d6d30b9ceecbc7762be7 MD5sum: 45401b0fff219489478c581175d6a8db Description: tools shipped with the GIFTI library GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package provides the tools that are shipped with the library (gifti_tool and gifti_test). Package: itksnap Version: 2.0.0-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 8100 Depends: libc6 (>= 2.3.6-6~), libfltk1.1 (>= 1.1.8~rc1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libinsighttoolkit3.16, libstdc++6 (>= 4.4.0), libvtk5.2 Homepage: http://www.itksnap.org Priority: extra Section: science Filename: pool/main/i/itksnap/itksnap_2.0.0-1~squeeze.nd1_i386.deb Size: 3605580 SHA256: 8493aceb93cc914d81743ef4829af80b93a91e31708d68f0f5b1c0b05b79653b SHA1: 7723e177b518cbc4e186e1fcb1321e427877c5ac MD5sum: b47c82156a98fc1f2c6720fa5cecb6c7 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 Package: kbibtex Version: 0.2.3-1~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 2548 Depends: kdelibs4c2a (>= 4:3.5.9), libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libqt3-mt (>= 3:3.3.8b), libstdc++6 (>= 4.1.1), libxml2 (>= 2.6.27), libxslt1.1 (>= 1.1.18) Recommends: texlive-bibtex-extra Suggests: texlive-latex-base | tetex-extra, bibtex2html, latex2rtf Homepage: http://www.unix-ag.uni-kl.de/~fischer/kbibtex Priority: optional Section: kde Filename: pool/main/k/kbibtex/kbibtex_0.2.3-1~squeeze.nd1_i386.deb Size: 784668 SHA256: 983e4e1e7b846ebdc732340e00f7274aa12d052a28178d3c2de8f70cff9ace07 SHA1: c4ad2445f44469f9f88b7100d92fcfc4b7cf2e5c MD5sum: 06fd2eb66cae4212965a588d1d843ab5 Description: BibTeX editor for KDE An application to manage bibliography databases in the BibTeX format. KBibTeX can be used as a standalone program, but can also be embedded into other KDE applications (e.g. as bibliography editor into Kile). . KBibTeX can query online ressources (e.g. Google scholar) via customizable search URLs. It is also able to import complete datasets from NCBI Pubmed. It also supports tagging references with keywords and manages references to local files. . BibTeX files can be exported into HTML, XML, PDF, PS and RTF format using a number of citation styles. Package: libbiosig-dev Source: biosig4c++ Version: 0.94.1+svn2521-1~pre0~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 1220 Homepage: http://biosig.sf.net/ Priority: extra Section: libdevel Filename: pool/main/b/biosig4c++/libbiosig-dev_0.94.1+svn2521-1~pre0~squeeze.nd1_i386.deb Size: 359398 SHA256: a3b9d513c0dc9870bfd0a526d1863e731cc38e6a7eb7ab8a50c781a055a191f8 SHA1: c65d3ddf0e7c623aae362124a9e6cdaab83e9fc0 MD5sum: efcb6b0a0cb81a5f2bf86c573990f03d Description: library for accessing files in biomedical data formats A library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://hci.tugraz.at/schloegl/biosig/TESTED . . This package provides header files and static library. Package: libbiosig0 Source: biosig4c++ Version: 0.94.1+svn2521-1~pre0~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 760 Depends: libc6 (>= 2.7), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1) Homepage: http://biosig.sf.net/ Priority: extra Section: libs Filename: pool/main/b/biosig4c++/libbiosig0_0.94.1+svn2521-1~pre0~squeeze.nd1_i386.deb Size: 283602 SHA256: f0045be22d183d196f02acc4bdb97b145cd0cb10880dfc7cd462806782781516 SHA1: 51c824e395dffe6ffcf75c45b0d772d0c70548ed MD5sum: 8998b7b3bf0643d09b8131c7840e51f2 Description: library for accessing files in biomedical data formats A library for accessing files in several biomedical data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://hci.tugraz.at/schloegl/biosig/TESTED . . This package provides dynamic library. Package: libgiftiio-dev Source: gifticlib Version: 1.0.9-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 204 Depends: libgiftiio0 (= 1.0.9-1~squeeze.nd1) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: libdevel Filename: pool/main/g/gifticlib/libgiftiio-dev_1.0.9-1~squeeze.nd1_i386.deb Size: 62812 SHA256: 867b6088809e2367db92779aa1e8c9a5f98eca61efe0c18a2291fbc0e7c6cbac SHA1: b4c327e2fa299bab3eb3f4c27c85b0460b315d89 MD5sum: 214ff5bda9d8062090d3ae5829931678 Description: IO library for the GIFTI cortical surface data format GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package provides the header files and static library. Package: libgiftiio0 Source: gifticlib Version: 1.0.9-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 172 Depends: libc6 (>= 2.3), libexpat1 (>= 1.95.8), libnifti2, zlib1g (>= 1:1.1.4) Homepage: http://www.nitrc.org/projects/gifti Priority: optional Section: libs Filename: pool/main/g/gifticlib/libgiftiio0_1.0.9-1~squeeze.nd1_i386.deb Size: 56988 SHA256: fc68dcc4aca8ef9560e7a28aea64c973dcb918c1622a0bfed92a4e75c89bbc6d SHA1: ee53dc464034c6835285763ad2ec9c1304e9f47e MD5sum: d4b070d164e9d57ca70ee9c08eea2ac6 Description: IO library for the GIFTI cortical surface data format GIFTI is an XML-based file format for cortical surface data. This reference IO implementation is developed by the Neuroimaging Informatics Technology Initiative (NIfTI). . This package contains the shared library. Package: libnifti-dev Source: nifticlib Version: 2.0.0-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 464 Depends: libnifti2 (= 2.0.0-1~squeeze.nd1) Conflicts: libfslio-dev, libnifti0-dev, libnifti1-dev, libniftiio-dev Replaces: libnifti1-dev Homepage: http://niftilib.sourceforge.net Priority: optional Section: libdevel Filename: pool/main/n/nifticlib/libnifti-dev_2.0.0-1~squeeze.nd1_i386.deb Size: 151338 SHA256: 5f907628840dd4c157d714c96ada28368996b5d6c343832dc553af1b0b9939ba SHA1: 479af124a523960bf9768f3756de0f64257947f7 MD5sum: d776ab112afb15d0006427f3117d330e Description: IO libraries for the NIfTI-1 data format Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the header files and static libraries of libniftiio, znzlib and libnifticdf. Package: libnifti-doc Source: nifticlib Version: 2.0.0-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1896 Homepage: http://niftilib.sourceforge.net Priority: optional Section: doc Filename: pool/main/n/nifticlib/libnifti-doc_2.0.0-1~squeeze.nd1_all.deb Size: 245414 SHA256: c421052431a49808544394d7242ddbd0437c09c001e9936fa302d29b653603d6 SHA1: 16d20e3475e20aaf39aa4df9231cb5117421d33d MD5sum: 1de8bde7f67f9fd2b7f2571ba0212457 Description: NIfTI library API documentation Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the library API reference documentation. Package: libnifti2 Source: nifticlib Version: 2.0.0-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 292 Depends: libc6 (>= 2.7), zlib1g (>= 1:1.1.4) Homepage: http://niftilib.sourceforge.net Priority: optional Section: libs Filename: pool/main/n/nifticlib/libnifti2_2.0.0-1~squeeze.nd1_i386.deb Size: 106516 SHA256: 4a3ebc725d6ab85147ceb4432313b46194831375f7a6af562f9eac768ffc6603 SHA1: 62fb913c4852564dc99b6f1a5f6091f4d17d652d MD5sum: 21fe0aa975d9290ecefb6c736cb3849e Description: IO libraries for the NIfTI-1 data format Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package contains the shared library of the low-level IO library niftiio, low-level IO library znzlib and the nifticdf shared library that provides functions to compute cumulative distributions and their inverses. Package: libodin-dev Source: odin Version: 1.8.1-3~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 15604 Homepage: http://od1n.sourceforge.net Priority: extra Section: libdevel Filename: pool/main/o/odin/libodin-dev_1.8.1-3~squeeze.nd1_i386.deb Size: 4026742 SHA256: 6f89e2583ac92cbd7d324e0a7bf6909d5c29ad684a9bed21f408b57017a62ffe SHA1: 30f15cf7d87d4454be0592d4ab5ab87de3a4b095 MD5sum: fe92a978a99660150718d9ef9ad315d1 Description: static libraries and header for ODIN sequences This package provides static libraries and headers of the ODIN libraries odindata, adinpara, odinqt, odinseq and tjutils. They are required for building magnetic resonance imaging (MRI) sequences with ODIN. Package: libopenmeeg-dev Source: openmeeg Version: 2.0.0.dfsg-2~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 276 Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: libdevel Filename: pool/main/o/openmeeg/libopenmeeg-dev_2.0.0.dfsg-2~squeeze.nd1_i386.deb Size: 43846 SHA256: 546ba87f48b6d6abb718419dd401d20e7463924a64cb4e3739317f455364b05c SHA1: 51f6f4a6a3a5060958acaa76c7b8ea10a041cf0f MD5sum: ccaa217b663c67df5f92bb9c73822f48 Description: library for solving EEG and MEG forward and inverse problems OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. . This package provides static libraries and header files. Package: libopenmeeg1 Source: openmeeg Version: 2.0.0.dfsg-2~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 824 Depends: libatlas3gf-base | liblapack3gf | liblapack.so.3gf, libatlas3gf-base | libblas3gf | libblas.so.3gf, libatlas3gf-base | libatlas.so.3gf, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libmatio0, libstdc++6 (>= 4.4.0) Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: science Filename: pool/main/o/openmeeg/libopenmeeg1_2.0.0.dfsg-2~squeeze.nd1_i386.deb Size: 231668 SHA256: 18f1715c33bdb4cf5a7d99f5a006be213b4b652e56bba86cd3a8f248b2973a7b SHA1: 2966ca93e525d0bf4f0dee0d86471a83ea18f99a MD5sum: 4d701bef8350e1078143ff1b73ba5bf7 Description: library for solving EEG and MEG forward and inverse problems OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. Package: libslicer3 Source: slicer Version: 3.4.0~svn10438-3~squeeze.nd1 Architecture: i386 Maintainer: Debian Science Team Installed-Size: 109604 Depends: libc6 (>= 2.3.6-6~), libcurl3 (>= 7.16.2-1), libgcc1 (>= 1:4.1.1), libgdcm2.0 (>= 2.0.12), libinsighttoolkit3.16, libkwwidgets1.0.0908, libstdc++6 (>= 4.1.1), libteem1 (>= 1.10.0), libvtk5.2, tcl8.5 (>= 8.5.0), vtk-tcl, zlib1g (>= 1:1.1.4) Homepage: http://www.slicer.org/ Priority: optional Section: libs Filename: pool/main/s/slicer/libslicer3_3.4.0~svn10438-3~squeeze.nd1_i386.deb Size: 25230644 SHA256: 0a5aef02cd1f481d15f853cb83fde6d34c21b2cc8c17bcb1b55e611db7b736e7 SHA1: b71c5599158dc1d45f6d7c311bda8b3978f2b33c MD5sum: a36e4011d8a5b77b8844383815b36bcb Description: software package for visualization and image analysis - runtime Slicer is an application for computer scientists and clinical researchers. The platform provides functionality for segmentation, registration and three-dimensional visualization of multi-modal image data, as well as advanced image analysis algorithms for diffusion tensor imaging, functional magnetic resonance imaging and image-guided therapy. Standard image file formats are supported, and the application integrates interface capabilities to biomedical research software and image informatics frameworks. . 3D Slicer libraries. Package: libslicer3-dev Source: slicer Version: 3.4.0~svn10438-3~squeeze.nd1 Architecture: i386 Maintainer: Debian Science Team Installed-Size: 3088 Depends: libslicer3 (= 3.4.0~svn10438-3~squeeze.nd1) Conflicts: libmrml1-dev Homepage: http://www.slicer.org/ Priority: optional Section: libdevel Filename: pool/main/s/slicer/libslicer3-dev_3.4.0~svn10438-3~squeeze.nd1_i386.deb Size: 446332 SHA256: 17bb3f3cb59d5a3f2f659f5deb7fe5f430042b3a1f11fd866a8554813a2a24c7 SHA1: b8d299264486671b5e088db0d9475cdb52a06cb0 MD5sum: 630b7119115ae8f53f2e78cb4728c658 Description: software package for visualization and image analysis - development Slicer is an application for computer scientists and clinical researchers. The platform provides functionality for segmentation, registration and three-dimensional visualization of multi-modal image data, as well as advanced image analysis algorithms for diffusion tensor imaging, functional magnetic resonance imaging and image-guided therapy. Standard image file formats are supported, and the application integrates interface capabilities to biomedical research software and image informatics frameworks. . 3D Slicer development files. Package: libvia-dev Source: via Version: 1.6.0-2~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 696 Depends: libvia0 (= 1.6.0-2~squeeze.nd1) Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: libdevel Filename: pool/main/v/via/libvia-dev_1.6.0-2~squeeze.nd1_i386.deb Size: 213252 SHA256: ae497c2d49da6add63f34cdc38e6ee626f653a5f45c3797f3d91c4b463736d47 SHA1: ce64b6edfc0ecca4d4d55fcdcabbac6c374f1ef2 MD5sum: 48455f9e52e3980683e3dfc42c85b549 Description: library for volumetric image analysis VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package provides the header files and static libraries of vialib, vxlib and viaio. Package: libvia-doc Source: via Version: 1.6.0-2~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 936 Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: doc Filename: pool/main/v/via/libvia-doc_1.6.0-2~squeeze.nd1_all.deb Size: 110492 SHA256: 4e8b7ff2508c5a1611f3b8c0a7187d504559a7afc6333b3cd00fa4f20fc4cc88 SHA1: 6153d1287d5042551385c28bd9e46c9b5258c390 MD5sum: 1e42168726e0b36b1b9c1aefec7a276f Description: VIA library API documentation VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package provides the library API reference documentation. Package: libvia0 Source: via Version: 1.6.0-2~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 440 Depends: lesstif2 (>= 1:0.94.4), libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.3), libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libsm6, libx11-6, libxext6, libxmu6, libxt6 Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: libs Filename: pool/main/v/via/libvia0_1.6.0-2~squeeze.nd1_i386.deb Size: 179612 SHA256: c43e468df2e6dbb08cfd296b00bf0b8a16e8e19ea0bf8e59bcafee1aedc629d4 SHA1: d51eea6874085fcf58f23cc6d3aa5a53dcba5cf6 MD5sum: ca7372905cb4b9fad56ebf481610227d Description: library for volumetric image analysis VIA is a volumetric image analysis suite. The included libraries provide about 70 image analysis functions. . This package contains the shared libraries of vialib, vxlib and viaio. Package: lipsia Version: 1.6.0-4~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 3448 Depends: libc6 (>= 2.7), libdcmtk1 (>= 3.5.4), libfftw3-3, libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libnifti2, libqt3-mt (>= 3:3.3.8b), libsm6, libstdc++6 (>= 4.4.0), libvia0, libx11-6, libxext6, zlib1g (>= 1:1.1.4), via-bin Recommends: dcmtk, lipsia-doc Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: science Filename: pool/main/l/lipsia/lipsia_1.6.0-4~squeeze.nd1_i386.deb Size: 1273038 SHA256: 92d251834c3ed15a8d3defdf58787e0297bade1a9f21247a5c17b88e53d5a480 SHA1: cff2550e197690bfaaec4e761179867019cc019f MD5sum: 97baff1322c502374375163975369928 Description: analysis suite for MRI and fMRI data Leipzig Image Processing and Statistical Inference Algorithms (LIPSIA) . This is a software package for the data processing and evaluation of functional magnetic resonance images. The analysis of fMRI data comprises various aspects including filtering, spatial transformation, statistical evaluation as well as segmentation and visualization. All these aspects are covered by LIPSIA. For the statistical evaluation, a number of well established and peer-reviewed algorithms were implemented in LIPSIA that allow an efficient and user-friendly processing of fMRI data sets. As the amount of data that must be handled is enormous, an important aspect in the development of LIPSIA was the efficiency of the software implementation. . LIPSIA operates exclusively on data in the VISTA data format. However, the package contains converters for medical image data in iBruker, ANALYZE and NIfTI format -- converting VISTA images into NIfTI files is also supported. Package: lipsia-doc Source: lipsia Version: 1.6.0-4~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 7004 Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: doc Filename: pool/main/l/lipsia/lipsia-doc_1.6.0-4~squeeze.nd1_all.deb Size: 5539242 SHA256: 698077dd0ec212ab7db8d81fb1ea253fde3176d0817184edf9cc35f1b634be0b SHA1: 9370ec74bf24fddf9143bc0556f7f3535560b929 MD5sum: 5d38c0c06db5d46971b92e261ab545db Description: documentation for LIPSIA Leipzig Image Processing and Statistical Inference Algorithms (LIPSIA) . This package provides the LIPSIA documentation in HTML format. Package: mitools Source: odin Version: 1.8.1-3~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 6236 Depends: libblitz0ldbl (>= 0.9), libc6 (>= 2.3.6-6~), libdcmtk1 (>= 3.5.4), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libnifti2, liboil0.3 (>= 0.3.10), libpng12-0 (>= 1.2.13-4), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libqwt5-qt4, libstdc++6 (>= 4.4.0), libvia0, libvtk5.4, zlib1g (>= 1:1.1.4), dcmtk Recommends: grace Homepage: http://od1n.sourceforge.net Priority: extra Section: science Filename: pool/main/o/odin/mitools_1.8.1-3~squeeze.nd1_i386.deb Size: 2378350 SHA256: 34169a7105b1e99036adcd851feb0f10d65b5373ad27dc029d5e3cd2ccf26313 SHA1: a6c58f078a5fb9c5b53cdb3aea709c18791e32fc MD5sum: 6e4f8ba474af1a3eddb3fdfb3187b033 Description: view, convert and perform basic maths with medical image datasets The three contained tools micalc, miconv and miview are handy command-line utilities for converting, manipulating and viewing medical image data in various formats (DICOM, NIfTI, PNG, binary data, ...). Package: mni-colin27-minc Source: mni-colin27 Version: 1.1-1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 12064 Homepage: http://packages.bic.mni.mcgill.ca/tgz/ Priority: extra Section: science Filename: pool/main/m/mni-colin27/mni-colin27-minc_1.1-1_all.deb Size: 12274320 SHA256: 53c6b97ed6d4182fd4da2502377bc1f32de4a816952eab6037e8791d85828fd0 SHA1: 467a57c00040530e387ed1183815d8591b32b2e6 MD5sum: 1ea73688b743b36778bee148076ebd4d Description: Talairach stereotaxic space template This template MRI volume was created from 27 T1-weighted MRI scans of a single individual that have been transformed into the Talairach stereotaxic space. The anatomical image is complemented by a brain and a head mask. All images are in 1x1x1 mm resolution. . This package provides the template in MINC format. Package: mni-colin27-nifti Source: mni-colin27 Version: 1.1-1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 11748 Homepage: http://packages.bic.mni.mcgill.ca/tgz/ Priority: extra Section: science Filename: pool/main/m/mni-colin27/mni-colin27-nifti_1.1-1_all.deb Size: 11952134 SHA256: 73bbe01f4f42fe966fc9308b46cedca16cda981da0492975afaaa9f731bf5581 SHA1: e1fa1c293312ea699493d2158efe70dd6649840e MD5sum: b9228cbbbd551e91de94f28d8f4da2ea Description: Talairach stereotaxic space template This template MRI volume was created from 27 T1-weighted MRI scans of a single individual that have been transformed into the Talairach stereotaxic space. The anatomical image is complemented by a brain and a head mask. All images are in 1x1x1 mm resolution. . This package provides the template in NIfTI format. Package: mni-icbm152-nlin-2009a Source: mni-icbm152-nlin Version: 0.20090623.1-1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 120332 Homepage: http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009 Priority: extra Section: science Filename: pool/main/m/mni-icbm152-nlin/mni-icbm152-nlin-2009a_0.20090623.1-1_all.deb Size: 122770998 SHA256: d1cab63c136b6898ce133ae0ac5309b77ac11774317e4710a3c567689bc64435 SHA1: 3c310421152cc482d8d99dca51d3c0145dab6553 MD5sum: dc79aa787955aa03e0d60c98cc5c3da3 Description: MNI stereotaxic space human brain template This is an unbiased standard magnetic resonance imaging template volume for the normal human population. It has been created by the Montreal Neurological Institute (MNI) using anatomical data from the International Consortium for Brain Mapping (ICBM). . The package provides a 1x1x1 mm resolution template (hemissphere-symetric and asymetric non-linearily co-registered versions), including T1w, T2w, PDw modalities, T2 relaxometry, and tissue probability maps. In addition, it contains a lobe atlas, and masks for brain, eyes and face. . The template is similar to the one in the mni-icbm152-nlin-2009c package. However, the sampling of the ICBM data is different and here intensity inhomogeneity correction was performed by N3 version 1.10.1, leading to different tissue probability maps. Package: mni-icbm152-nlin-2009b Source: mni-icbm152-nlin Version: 0.20090623.1-1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 722392 Homepage: http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009 Priority: extra Section: science Filename: pool/main/m/mni-icbm152-nlin/mni-icbm152-nlin-2009b_0.20090623.1-1_all.deb Size: 739142896 SHA256: d00b100f1a65e1e3909adddd1f9a9d3fb4c717ced6f425089a276b64780cd13d SHA1: 5d4b4d340be14ed062a5e96bc43af33d2fd9ec40 MD5sum: 0e906ff84b016a127d7cc1ecf03dfbef Description: MNI stereotaxic space human brain template This is an unbiased standard magnetic resonance imaging template volume for the normal human population. It has been created by the Montreal Neurological Institute (MNI) using anatomical data from the International Consortium for Brain Mapping (ICBM). . The package provides a 0.5x0.5x0.5 mm resolution template (hemissphere-symetric and asymetric non-linearily co-registered versions), including T1w, T2w, PDw modalities. Package: mni-icbm152-nlin-2009c Source: mni-icbm152-nlin Version: 0.20090623.1-1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 113888 Homepage: http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009 Priority: extra Section: science Filename: pool/main/m/mni-icbm152-nlin/mni-icbm152-nlin-2009c_0.20090623.1-1_all.deb Size: 116182926 SHA256: 08c25ff6564fd6860d96bf32a182ce5922aaadd2b584850d82762aa9bb4fefd5 SHA1: f515a99b9edc7dfabfb058a21acbab12a2031c1a MD5sum: c1ec21de0bd62ab68c1d2a84655d4891 Description: MNI stereotaxic space human brain template This is an unbiased standard magnetic resonance imaging template volume for the normal human population. It has been created by the Montreal Neurological Institute (MNI) using anatomical data from the International Consortium for Brain Mapping (ICBM). . The package provides a 1x1x1 mm resolution template (hemissphere-symetric and asymetric non-linearily co-registered versions), including T1w, T2w, PDw modalities, and tissue probability maps. In addition, it contains a lobe atlas, and masks for brain, eyes and face. . The template is similar to the one in the mni-icbm152-nlin-2009a package. However, the sampling of the ICBM data is different and here intensity inhomogeneity correction was performed by N3 version 1.11, leading to different tissue probability maps. Package: mricron Version: 0.20100820.1~dfsg.1-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 10732 Depends: libatk1.0-0 (>= 1.29.3), libc6 (>= 2.3.6-6~), libcairo2 (>= 1.2.4), libglib2.0-0 (>= 2.12.0), libgtk2.0-0 (>= 2.8.0), libpango1.0-0 (>= 1.14.0), libx11-6, mricron-data Suggests: mricron-doc Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron_0.20100820.1~dfsg.1-1~squeeze.nd1_i386.deb Size: 4051604 SHA256: 52ecb5b44f1caad9e6047ad8c6b069933387ec8a11d7b564f7924059d0310d78 SHA1: 9ccd28c3bd94d75749163d21f0c4605fb2c92383 MD5sum: de1cad834de2909bbdfda9162b14d127 Description: magnetic resonance image conversion, viewing and analysis This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . In addition to 'mricron', this package also provides 'dcm2nii' that supports converting DICOM and PAR/REC images into the NIfTI format, and 'npm' for non-parametric data analysis. Package: mricron-data Source: mricron Version: 0.20100820.1~dfsg.1-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1852 Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: science Filename: pool/main/m/mricron/mricron-data_0.20100820.1~dfsg.1-1~squeeze.nd1_all.deb Size: 1665586 SHA256: b54a9281f6e837bcbe89e6eed783b51ddb20043a1bcdf1c445b43c95c45cca17 SHA1: 6171525fe72ac7b5fba85fb25a4c98ae5e4654a7 MD5sum: cf07cd57a543330215c0c9d099ddaf80 Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides data files for MRIcron, such as brain atlases, anatomy, and color schemes. Package: mricron-doc Source: mricron Version: 0.20100820.1~dfsg.1-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1220 Homepage: http://www.cabiatl.com/mricro/mricron/index.html Priority: extra Section: doc Filename: pool/main/m/mricron/mricron-doc_0.20100820.1~dfsg.1-1~squeeze.nd1_all.deb Size: 737212 SHA256: 1f8ad7d06506620e92d63abf0b2f7c4bc17f20b9e01cdac9d97ac1bbee9185aa SHA1: 08329e18e9d54bc7df6aaf93a03b76979a8a11d7 MD5sum: b75c3faabb1e8db4e9324ef4b62e2a45 Description: data files for MRIcron This is a GUI-based visualization and analysis tool for (functional) magnetic resonance imaging. MRIcron can be used to create 2D or 3D renderings of statistical overlay maps on brain anatomy images. Moreover, it aids drawing anatomical regions-of-interest (ROI), or lesion mapping, as well as basic analysis of functional timeseries (e.g. creating plots of peristimulus signal-change). . This package provides documentation for MRIcron in HTML format. Package: mrtrix Version: 0.2.8-1~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 6512 Depends: libatk1.0-0 (>= 1.29.3), libc6 (>= 2.3.6-6~), libcairo2 (>= 1.2.4), libcairomm-1.0-1 (>= 1.6.4), libfontconfig1 (>= 2.8.0), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libglibmm-2.4-1c2a (>= 2.24.0), libglu1-mesa | libglu1, libgsl0ldbl (>= 1.9), libgtk2.0-0 (>= 2.8.0), libgtkglext1, libgtkmm-2.4-1c2a (>= 1:2.20.0), libice6 (>= 1:1.0.0), libpango1.0-0 (>= 1.14.0), libpangomm-1.4-1 (>= 2.26.0), libsigc++-2.0-0c2a (>= 2.0.2), libsm6, libstdc++6 (>= 4.3), libx11-6, libxmu6, libxt6 Suggests: mrtrix-doc Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: science Filename: pool/main/m/mrtrix/mrtrix_0.2.8-1~squeeze.nd1_i386.deb Size: 2250466 SHA256: ae948c9ab666dbd42aff704594fbb6858e1cc0c2d18b9c60ee0a37121e182a4c SHA1: 64492444735232232988b625800074c9e17fa115 MD5sum: c785742c118425b534d5bb9944f29663 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. Magenetic resonance images in DICOM or ANALYZE format are supported. Package: mrtrix-doc Source: mrtrix Version: 0.2.8-1~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 3416 Homepage: http://www.brain.org.au/software/mrtrix Priority: extra Section: doc Filename: pool/main/m/mrtrix/mrtrix-doc_0.2.8-1~squeeze.nd1_all.deb Size: 2949200 SHA256: d09abc3e306bb2c180870e91d45439b7a3c4e7b63e0991af6a1a6df4b1e55274 SHA1: aaf46c988af9be0c7145312f44a0db291fc1fe07 MD5sum: 3185125d78f719d3942d277b91c59c5c Description: documentation for mrtrix 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. Magenetic resonance images in DICOM or ANALYZE format are supported. . This package provides the documentation in HTML format. Package: nifti-bin Source: nifticlib Version: 2.0.0-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 188 Depends: libc6 (>= 2.7), libnifti2 Homepage: http://niftilib.sourceforge.net Priority: optional Section: utils Filename: pool/main/n/nifticlib/nifti-bin_2.0.0-1~squeeze.nd1_i386.deb Size: 59178 SHA256: 2990e1363bb38f8f721f787c5728027dcf4eb56c6594cf5da39bda4cac9ec909 SHA1: 5eb049efc861aedebf8260759171d809cb4e8bb5 MD5sum: 18a4ed953057c85252118ddacd512538 Description: tools shipped with the NIfTI library Niftilib is a set of i/o libraries for reading and writing files in the NIfTI-1 data format. NIfTI-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images. . This package provides the tools that are shipped with the library (nifti_tool, nifti_stats and nifti1_test). Package: octave-biosig Source: biosig4c++ Version: 0.94.1+svn2521-1~pre0~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 1396 Depends: libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libfftw3-3, libgcc1 (>= 1:4.1.1), libgfortran3 (>= 4.3), libhdf5-serial-1.8.4 | libhdf5-1.8.4, liblapack3gf | liblapack.so.3gf | libatlas3gf-base, libncurses5 (>= 5.7+20100313), libreadline6 (>= 6.0), libstdc++6 (>= 4.2.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: science Filename: pool/main/b/biosig4c++/octave-biosig_0.94.1+svn2521-1~pre0~squeeze.nd1_i386.deb Size: 546154 SHA256: 2998eba1552a3fff51765e7bcb0966bc54fb1e9f420e3c58d30798c70f5e3d6a SHA1: e22dfaf66deb57fd5092f717d468ee2e2664722e MD5sum: 07b58a9a4a5fd5c315ea67769e31a93b Description: Octave bindings for BioSig4C++ library This package provides Octave bindings for biosig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDlibbiosig4c++. Package: odin Version: 1.8.1-3~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 4000 Depends: libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libqtcore4 (>= 4:4.5.3), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.4.0), libvtk5.4, mitools (= 1.8.1-3~squeeze.nd1), libodin-dev, libgsl0-dev, libc6-dev | libc-dev, g++, libblas-dev | libatlas-base-dev, xterm | x-terminal-emulator, gdb Recommends: liboil0.3-dev | liboil-dev, libdcmtk1-dev Homepage: http://od1n.sourceforge.net Priority: extra Section: science Filename: pool/main/o/odin/odin_1.8.1-3~squeeze.nd1_i386.deb Size: 1547432 SHA256: 023ad14334f378adad8d680c8e6e1372821795ec064fe05ac85a09fea9b7dd15 SHA1: 899697a83502d5a8e20e5fcbfd07ca82932e50b8 MD5sum: e076da095a8af0280156721535f83e6d Description: develop, simulate and run magnetic resonance sequences ODIN is a framework for magnetic resonance imaging (MRI). It covers the whole toolchain of MRI, from low-level data acquisition to image reconstruction. In particular, it aims at rapid prototyping of MRI sequences. The sequences can be programmed using a high-level, object oriented, C++ programming interface. It provides advanced sequence analysis tools, such as interactive plotting of k-space trajectories, a user interface for a fast compile-link-test cycle and a powerful MRI simulator which supports different virtual samples. For fast and flexible image reconstruction, ODIN contains a highly customizable, multi-threaded data-processing framework. Package: openelectrophy Version: 0.0.svn143-1~squeeze.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 92 Depends: python, python-pyssdh (= 0.0.svn143-1~squeeze.nd1) Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: science Filename: pool/main/o/openelectrophy/openelectrophy_0.0.svn143-1~squeeze.nd1_all.deb Size: 34368 SHA256: d3c29b416792bf1d8ca68eb2af7da3b0d60a8f0d836fa9d1d3b83cdd9329b878 SHA1: 1f8d2aca09d37c8e5efb01093a0e10909a862e38 MD5sum: 78bfb172b4686b3985ab9ee42929d028 Description: data analysis framework for intra- and extra-cellular recordings This software aims to simplify data and analysis sharing for intra- and extra-cellular recordings. It supports time frequency plots, spike detection, spike rate calculation, and analysis of phase locked signals. . Data handling and storage utilizes a MySQL database, allowing to handle large amounts of data easily and efficiently. Therefore, a MySQL server running locally or on a remote machine is required. . This package provides the OpenElectrophy GUI. Package: openmeeg-tools Source: openmeeg Version: 2.0.0.dfsg-2~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 508 Depends: libatlas3gf-base | libblas3gf | libblas.so.3gf, libatlas3gf-base | liblapack3gf | liblapack.so.3gf, libatlas3gf-base | libatlas.so.3gf, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libmatio0, libopenmeeg1, libstdc++6 (>= 4.4.0) Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: science Filename: pool/main/o/openmeeg/openmeeg-tools_2.0.0.dfsg-2~squeeze.nd1_i386.deb Size: 156402 SHA256: 10dc0db89f70a27666075a1615e2645a63c0d2ca92fd7a3dc735a59306523acb SHA1: 4c1bccf958103eb183df95aff361645a39d1861e MD5sum: 37b27995309b30edc4e9a6f2513e34b2 Description: tools for solving EEG and MEG forward and inverse problems OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. . This package provides command line tools. Package: psychopy Version: 1.62.01.dfsg-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3124 Depends: python (>= 2.4), python-support (>= 0.90.0), python-pyglet | python-pygame, python-opengl, python-numpy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-imaging, python-serial, python-scipy, libavbin0 Suggests: python-iolabs, python-pyepl Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.62.01.dfsg-1~squeeze.nd1_all.deb Size: 1393748 SHA256: 730417a5d57a5372f4edb41a63020771dc07c3bdc03d81ecb0af84daf9068e08 SHA1: de0db569a1e5d1e25f6a6e577bd17844c17683c6 MD5sum: 15f2426e137673252516036a90abadba Description: environment for creating psychology stimuli in Python PsychoPy provides an environment for creating psychology stimuli using Python scripting language. It combines the graphical strengths of OpenGL with easy Python syntax to give psychophysics a free and simple stimulus presentation and control package. . The goal is to provide, for the busy scientist, tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. PsychoPy features - High-level powerful scripting language (Python) - Simple syntax - Use of hardware-accelerated graphics (OpenGL) - Integration with Spectrascan PR650 for easy monitor calibration - Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping - Simple (or complex) GUIs via wxPython - Easy interfaces to joysticks, mice, sound cards etc. via PyGame - Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli Python-Version: 2.5, 2.6 Package: python-biosig Source: biosig4c++ Version: 0.94.1+svn2521-1~pre0~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 908 Depends: libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), zlib1g (>= 1:1.1.4) Homepage: http://biosig.sf.net/ Priority: extra Section: python Filename: pool/main/b/biosig4c++/python-biosig_0.94.1+svn2521-1~pre0~squeeze.nd1_i386.deb Size: 316964 SHA256: 6f0fad49e2045bfe464c844d2c67dccdeacaf1068a322bdf5ebb5018cd61ee34 SHA1: 72de61ec191df1f7b666955902e640bc64e481fd MD5sum: c4925af7f0d2df60c2a357add20e0253 Description: Python bindings for BioSig4C++ library This package provides Python bindings for biosig library. Primary goal -- I/O interface to variety of biomedical file formats, including but not limited to SCP-ECG(EN1064), HL7aECG (FDA-XML), GDF, EDlibbiosig4c++. Package: python-dicom Source: pydicom Version: 0.9.5~rc1-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1864 Depends: python (>= 2.5), python-support (>= 0.90.0) Recommends: python-numpy, python-imaging Suggests: python-matplotlib Homepage: http://code.google.com/p/pydicom/ Priority: optional Section: python Filename: pool/main/p/pydicom/python-dicom_0.9.5~rc1-1~squeeze.nd1_all.deb Size: 372934 SHA256: 86c7cf926457b1ee202649b15563e1cc5f38003f0b12acd47b0f912fe7ba3349 SHA1: 69ded2a0cb005e606fdb53ae5c7d2812a9e08955 MD5sum: 18025a434efb994467d69e223bd17d6d Description: DICOM medical file reading and writing pydicom is a pure Python module for parsing DICOM files. DICOM is a standard (http://medical.nema.org) for communicating medical images and related information such as reports and radiotherapy objects. . pydicom makes it easy to read DICOM files into natural pythonic structures for easy manipulation. Modified datasets can be written again to DICOM format files. Package: python-mdp Source: mdp Version: 2.6-1~squeeze.nd1 Architecture: all Maintainer: Yaroslav Halchenko Installed-Size: 1556 Depends: python (>= 2.4), python-support (>= 0.90.0), python-numpy Recommends: python-scipy, python-shogun-modular, python-libsvm Suggests: python-pp Enhances: python-mvpa Homepage: http://mdp-toolkit.sourceforge.net/ Priority: optional Section: python Filename: pool/main/m/mdp/python-mdp_2.6-1~squeeze.nd1_all.deb Size: 294380 SHA256: 1d403d11e45a5d05547ac32e8439992606ef2abc1d9550ead40f002d6dba14ff SHA1: 7ab2a574969ba070fe840595ae9ba6331e89e15e MD5sum: d29feeab68e19fed325a6b2d25338677 Description: Modular toolkit for Data Processing Python data processing framework. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Independent Slow Feature Analysis (ISFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA), and Gaussian Classifiers. Package: python-mlpy Source: mlpy Version: 2.2.0~dfsg1-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 428 Depends: python (>= 2.4), python-support (>= 0.90.0), python2.6, python-numpy, python-mlpy-lib (>= 2.2.0~dfsg1-1~squeeze.nd1) Suggests: python-mvpa Provides: python2.5-mlpy, python2.6-mlpy Homepage: https://mlpy.fbk.eu/ Priority: optional Section: python Filename: pool/main/m/mlpy/python-mlpy_2.2.0~dfsg1-1~squeeze.nd1_all.deb Size: 58266 SHA256: 77f4b8e2129db61e00feaad3c1460a923975820c91e625dc4fff605039f14c7a SHA1: 878fa1b9c71726e276b82d462006a5a90c127ea6 MD5sum: 69d292f9dfb2f666d6a3542ddbe60dd3 Description: high-performance Python package for predictive modeling mlpy provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for preprocessing, clustering, predictive classification and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping. . mlpy includes: SVM (Support Vector Machine), KNN (K Nearest Neighbor), FDA, SRDA, PDA, DLDA (Fisher, Spectral Regression, Penalized, Diagonal Linear Discriminant Analysis) for classification and feature weighting, I-RELIEF, DWT and FSSun for feature weighting, *RFE (Recursive Feature Elimination) and RFS (Recursive Forward Selection) for feature ranking, DWT, UWT, CWT (Discrete, Undecimated, Continuous Wavelet Transform), KNN imputing, DTW (Dynamic Time Warping), Hierarchical Clustering, k-medoids, Resampling Methods, Metric Functions, Canberra indicators. Python-Version: 2.5, 2.6 Package: python-mlpy-doc Source: mlpy Version: 2.2.0~dfsg1-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1136 Depends: libjs-jquery Suggests: python-mlpy Homepage: https://mlpy.fbk.eu/ Priority: optional Section: doc Filename: pool/main/m/mlpy/python-mlpy-doc_2.2.0~dfsg1-1~squeeze.nd1_all.deb Size: 480866 SHA256: a1a158d0318129c2b6ac767cf0385b266a45aeaa6a06a45fc5bf61d6a77ff9b5 SHA1: 0de7a2884bfd8de60215558a742d138d0d35f167 MD5sum: 676b76390bb77f41f7a1ee949b11e212 Description: documention and examples for mlpy mlpy provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for preprocessing, clustering, predictive classification and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping. . This package provides user documentation for mlpy in various formats (HTML, PDF). Package: python-mlpy-lib Source: mlpy Version: 2.2.0~dfsg1-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 448 Depends: libc6 (>= 2.3.6-6~), libgsl0ldbl (>= 1.9), python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python-numpy Provides: python2.5-mlpy-lib, python2.6-mlpy-lib Homepage: https://mlpy.fbk.eu/ Priority: optional Section: python Filename: pool/main/m/mlpy/python-mlpy-lib_2.2.0~dfsg1-1~squeeze.nd1_i386.deb Size: 121286 SHA256: 2e849443ca2e80a1704bf50b280d59b1c050aba414752bfa555eb9b04be6a333 SHA1: e748d227727cc8b0fd91b5afaf9696187ed0d009 MD5sum: 7374f7da64d5a4e499f367af961ad901 Description: low-level implementations and bindings for mlpy This is an add-on package for the mlpy providing compiled core functionality. Python-Version: 2.5, 2.6 Package: python-mvpa Source: pymvpa Version: 0.4.4-1~squeeze.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 4152 Depends: python (>= 2.5), python-support (>= 0.90.0), python2.6, python-numpy, python-mvpa-lib (>= 0.4.4-1~squeeze.nd1) Recommends: python-nifti, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab Suggests: fslview, fsl, python-nose, python-lxml, python-openopt, python-rpy, python-mvpa-doc Provides: python2.5-mvpa, python2.6-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa_0.4.4-1~squeeze.nd1_all.deb Size: 2164768 SHA256: 4ab18cc800964eb51d43bd27e2cba0d6bc09a294b884f05793fe01f3a32076b4 SHA1: 3d1a857903184e8773466dd13bfd2751823b6672 MD5sum: 53c98d112e1f7ed4feb689024914d58a Description: multivariate pattern analysis with Python Python module to ease pattern classification analyses of large datasets. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, GNB, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. Python-Version: 2.5, 2.6 Package: python-mvpa-doc Source: pymvpa Version: 0.4.4-1~squeeze.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 43808 Depends: libjs-jquery Suggests: python-mvpa Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa/python-mvpa-doc_0.4.4-1~squeeze.nd1_all.deb Size: 9836754 SHA256: d99b779d1916a7504a4dce85685520bd6410c1df988101feb3a8e606511fac01 SHA1: 2a58015dfe237fe73b1ec6b2933a33a68491530d MD5sum: d1ff42df2b1f3393567998ff5c0dc267 Description: documentation and examples for PyMVPA PyMVPA documentation in various formats (HTML, TXT) including * User manual * Developer guidelines * API documentation . Additionally, all example scripts shipped with the PyMVPA sources are included. Package: python-mvpa-lib Source: pymvpa Version: 0.4.4-1~squeeze.nd1 Architecture: i386 Maintainer: Experimental Psychology Maintainers Installed-Size: 284 Depends: libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm2, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python-numpy Provides: python2.5-mvpa-lib, python2.6-mvpa-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa/python-mvpa-lib_0.4.4-1~squeeze.nd1_i386.deb Size: 65994 SHA256: 0c5793239acbf6c828c5ae678924b70cf6e53e1b22f00d7aa098cfe90dac5ccd SHA1: 14de3e08af1d55867d23d52240b0b4f80643b75d MD5sum: e0ce2075bdc4fc4f9fc87d43ad678127 Description: low-level implementations and bindings for PyMVPA This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. Python-Version: 2.5, 2.6 Package: python-mvpa-snapshot Source: pymvpa-snapshot Version: 0.5.0.dev+783+gde39-1~squeeze.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 4432 Depends: python (>= 2.4), python-support (>= 0.90.0), python2.6, python-numpy, python-mvpa-snapshot-lib (>= 0.5.0.dev+783+gde39-1~squeeze.nd1) Recommends: python-nifti, python-psyco, python-mdp, python-scipy, shogun-python-modular, python-pywt, python-matplotlib, python-reportlab Suggests: fslview, fsl, python-nose, python-lxml, python-scikits-openopt, python-rpy, python-mvpa-doc Conflicts: python-mvpa Provides: python2.5-mvpa-snapshot, python2.6-mvpa-snapshot Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa-snapshot/python-mvpa-snapshot_0.5.0.dev+783+gde39-1~squeeze.nd1_all.deb Size: 2225732 SHA256: 8fcc157f8ade8933df659309e098ececab096d4e5cf0b5985fb327d5b76f1198 SHA1: 36154262bc56ab8da032948dd7e263d91717f5e1 MD5sum: f51bf1e5c614bdefb50a5b991de50f38 Description: multivariate pattern analysis with Python Python module to ease pattern classification analyses of large datasets. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. . This is a package of a development snaphot. The latest released version is provided by the python-mvpa package. Python-Version: 2.5, 2.6 Package: python-mvpa-snapshot-lib Source: pymvpa-snapshot Version: 0.5.0.dev+783+gde39-1~squeeze.nd1 Architecture: i386 Maintainer: Experimental Psychology Maintainers Installed-Size: 284 Depends: libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.1.1), libsvm2, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python-numpy Conflicts: python-mvpa-lib Provides: python2.5-mvpa-snapshot-lib, python2.6-mvpa-snapshot-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa-snapshot/python-mvpa-snapshot-lib_0.5.0.dev+783+gde39-1~squeeze.nd1_i386.deb Size: 66086 SHA256: 13815fc25bb3ada4fd0ee7d249372847e0724cd2badd7891f3b794100f590c88 SHA1: 6cdedd4b7ed404584ba642d7c13c1f013c5f00cf MD5sum: 96453f7a2a366135a015a61504d25c95 Description: low-level implementations and bindings for PyMVPA This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snaphot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.5, 2.6 Package: python-networkx Version: 1.0.1-0.1~squeeze.nd1 Architecture: all Maintainer: Cyril Brulebois Installed-Size: 1980 Depends: python (>= 2.4), python-support (>= 0.90.0) Recommends: python-numpy, python-scipy, python-pygraphviz | python-pydot, python-pkg-resources, python-matplotlib, python-yaml Homepage: https://networkx.lanl.gov/ Priority: optional Section: python Filename: pool/main/p/python-networkx/python-networkx_1.0.1-0.1~squeeze.nd1_all.deb Size: 537842 SHA256: 0bed24d1ae233d484992277c1fe58619219db67e87bac47de4fc473273176410 SHA1: 980c0931aeac54c6e394c703d1df2ea1e707c551 MD5sum: cf2df0438a30f01ce5280ba618df0c82 Description: tool to manipulate and study more than complex networks NetworkX is a Python-based package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. . The structure of a graph or network is encoded in the edges (connections, links, ties, arcs, bonds) between nodes (vertices, sites, actors). If unqualified, by graph we mean a simple undirected graph, i.e. no self-loops and no multiple edges are allowed. By a network we usually mean a graph with weights (fields, properties) on nodes and/or edges. . The potential audience for NetworkX includes: mathematicians, physicists, biologists, computer scientists, social scientists. Package: python-nibabel-snapshot Source: nibabel-snapshot Version: 1.0.0.dev+137+gf1c6-1~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 964 Depends: python (>= 2.5), python-support (>= 0.90.0), python-numpy, libjs-jquery, python-scipy Conflicts: python-nibabel Provides: python2.5-nibabel-snapshot, python2.6-nibabel-snapshot Homepage: http://nipy.sourceforge.net/nibabel Priority: optional Section: python Filename: pool/main/n/nibabel-snapshot/python-nibabel-snapshot_1.0.0.dev+137+gf1c6-1~squeeze.nd1_all.deb Size: 469788 SHA256: 88f8f2603bab6606985a137433460486b70e5765b08eba1ca81b8dccd3cfe96f SHA1: 12bd934e7cec2d24b9aec58fd66b592b9b4be485 MD5sum: feea254498444cc7f9827456091e83dc Description: Python bindings to various neuroimaging data formats Currently supported formats are: . * ANALYZE (including SPM2 and SPM99 variants) * MINC * NIfTI * PAR/REC . This package also provides a commandline tool for conversion of PAR/REC to NIfTI images. Python-Version: 2.5, 2.6 Package: python-nifti Source: pynifti Version: 0.20100607.1-2~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 1416 Depends: libc6 (>= 2.3.6-6~), libnifti2, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python2.6, python-numpy, libjs-jquery Provides: python2.5-nifti, python2.6-nifti Homepage: http://niftilib.sourceforge.net/pynifti/ Priority: optional Section: python Filename: pool/main/p/pynifti/python-nifti_0.20100607.1-2~squeeze.nd1_i386.deb Size: 344682 SHA256: d1d670f3c7b5ce720fec8d6452905a8a16be55c41ee158321a3ff9d639e61eb3 SHA1: 8972416b2e0e5e11e32fdff9b39eec4f2b3899f0 MD5sum: 4b407502a42e35faefe1e7ba214d416b Description: Python interface to the NIfTI I/O libraries Using PyNIfTI one can easily read and write NIfTI and ANALYZE images from within Python. The NiftiImage class provides Python-style access to the full header information. Image data is made available via NumPy arrays. Python-Version: 2.5, 2.6 Package: python-nipype Source: nipype Version: 0.3.3-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1752 Depends: python (>= 2.5), python-support (>= 0.90.0), python-scipy, python-simplejson, python-traits Recommends: python-nifti, ipython, python-nose, python-networkx Suggests: fsl, afni, lipsia, python-nipy Provides: python2.5-nipype, python2.6-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: python Filename: pool/main/n/nipype/python-nipype_0.3.3-1~squeeze.nd1_all.deb Size: 277528 SHA256: c9f658b7045c47f30bcd1c4c1003dc84d177e5cc973e08e8ad828dec772369b0 SHA1: 62aebb706464818ddca13f1edf064820fc0f4088 MD5sum: 14644333145064a6db9f43cd16b3c14a Description: Neuroimaging data analysis pipelines in Python Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). Package: python-nipype-doc Source: nipype Version: 0.3.3-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 3640 Depends: libjs-jquery Suggests: python-nipype Homepage: http://nipy.sourceforge.net/nipype/ Priority: optional Section: doc Filename: pool/main/n/nipype/python-nipype-doc_0.3.3-1~squeeze.nd1_all.deb Size: 840654 SHA256: 3c415531033955e31045f2db2f1edfd51dc65ccb1ce51dae7ced1899625d79a6 SHA1: 1262afc30d40e8b74698fbdffa6e0b6d1f8a0537 MD5sum: 8a1e7f0cc079faf07940c344e85d63e0 Description: Neuroimaging data analysis pipelines in Python -- documentation Nipype interfaces Python to other neuroimaging packages and creates an API for specifying a full analysis pipeline in Python. Currently, it has interfaces for SPM, FSL, AFNI, Freesurfer, but could be extended for other packages (such as lipsia). . This package contains Nipype examples and documentation in various formats. Package: python-openmeeg Source: openmeeg Version: 2.0.0.dfsg-2~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 556 Depends: libatlas3gf-base | libblas3gf | libblas.so.3gf, libatlas3gf-base | liblapack3gf | liblapack.so.3gf, libatlas3gf-base | libatlas.so.3gf, libc6 (>= 2.1.3), libgcc1 (>= 1:4.1.1), libmatio0, libopenmeeg1, libpython2.6 (>= 2.6), libstdc++6 (>= 4.4.0), python (<< 2.7), python (>= 2.6), python-support (>= 0.90.0), python-numpy Provides: python2.6-openmeeg Homepage: http://www-sop.inria.fr/odyssee/software/OpenMEEG/ Priority: extra Section: python Filename: pool/main/o/openmeeg/python-openmeeg_2.0.0.dfsg-2~squeeze.nd1_i386.deb Size: 153972 SHA256: aeeeb361675bc14b65e40b84e71faa94fb90d1303a1cfa39882b596565d95058 SHA1: 23b0dd3b92dc5b1b7d69f419c56f6010e7a91259 MD5sum: d0649020c8172b35c4954bc196e7647e Description: Python bindings for openmeeg library OpenMEEG provides state-of-the art tools for processing EEG and MEG data. . The forward problem is implemented using the symmetric Boundary Element method [Kybic et al, 2005], providing excellent accuracy, particularly for superficial cortical sources. The source localization procedures implemented in OpenMEEG are based on a distributed source model, with three different types of regularization: the Minimum Norm, and the L2 and L1 norms of the surface gradient of the sources [Adde et al, 2005]. . This package provides Python bindings for OpenMEEG library. Python-Version: 2.6 Package: python-openpyxl Source: openpyxl Version: 1.1.0-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 448 Depends: python, python-support (>= 0.90.0) Recommends: python-nose Homepage: http://bitbucket.org/ericgazoni/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_1.1.0-1~squeeze.nd1_all.deb Size: 49184 SHA256: 7edf6c44f034197891e558f2dbe31136fbc4aa7f81257afea99d286d14729d88 SHA1: 913e4bee3b1f7bbfa4836583ceeba683da382cf0 MD5sum: c2217c8d63f12b262b1af9e1424d8fe2 Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python-pyepl Source: pyepl Version: 1.1.0-3~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 2164 Depends: python (<< 2.7), python (>= 2.5), python-central (>= 0.6.11), python-pyepl-common (= 1.1.0-3~squeeze.nd1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libasound2 (>> 1.0.18), libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libode1, libsamplerate0, libsndfile1 (>= 1.0.20), libstdc++6 (>= 4.4.0) Conflicts: python2.3-pyepl, python2.4-pyepl Replaces: python2.3-pyepl, python2.4-pyepl Provides: python2.5-pyepl, python2.6-pyepl Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl_1.1.0-3~squeeze.nd1_i386.deb Size: 536326 SHA256: 78e856106e6abb8c0324b82bc5579ae79d64e8a696b260d7faa2a97362f50119 SHA1: fd989302b24fc3e0eb16e99bbe1c022fd3a90344 MD5sum: 6934b01474a73e988c149a4baa988e43 Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides PyEPL for supported versions of Python. Python-Version: 2.5, 2.6 Package: python-pyepl-common Source: pyepl Version: 1.1.0-3~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 852 Depends: python Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl-common_1.1.0-3~squeeze.nd1_all.deb Size: 817820 SHA256: 575a264fe983d8b7d0ad9eaac6baae7c46308bfea1a454dd466636f7cd9b60da SHA1: 219e559bf4ac39efbc3f0e375cf3ea8849d1d224 MD5sum: b3492c37881b41822afe7760f1b3cc5a Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides common files such as images. Package: python-pyoptical Source: pyoptical Version: 0.2-1~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 72 Depends: python-serial Enhances: psychopy, python-pyepl Homepage: http://github.com/esc/pyoptical Priority: extra Section: python Filename: pool/main/p/pyoptical/python-pyoptical_0.2-1~squeeze.nd1_all.deb Size: 6956 SHA256: 66717fa53f6d283a3a697f969f32bc1c15f1467bbc26bb09ffceba7beb871644 SHA1: 3201dafeb370ade84db53fbe0ce85c1a0e57455c MD5sum: cf68976930753cdd2fde4b74529ba1b6 Description: python interface to the CRS 'OptiCAL' photometer The 'OptiCAL' is a photometer that is produced by Cambridge Research Systems (CRS). This device is a standard tool for gamma-calibration of display devices in vision research. This package provides a free-software replacement for the Windows-software distributed by the manufacturer that allows querying an OptiCAL via a serial connection. pyoptical can be used as a library for third-party applications or as a standalone command line tool. Python-Version: 2.5, 2.6 Package: python-pyssdh Source: openelectrophy Version: 0.0.svn143-1~squeeze.nd1 Architecture: all Maintainer: Experimental Psychology Maintainers Installed-Size: 792 Depends: python-support (>= 0.90.0), python-numpy, python-scipy, python-qt4, python-mysqldb, python-matplotlib Recommends: g++ | c++-compiler, python-mdp Suggests: mysql-server Provides: python2.4-pyssdh, python2.5-pyssdh Homepage: http://neuralensemble.org/trac/OpenElectrophy Priority: extra Section: python Filename: pool/main/o/openelectrophy/python-pyssdh_0.0.svn143-1~squeeze.nd1_all.deb Size: 119516 SHA256: 1adaffa1132d6581ae599f8781f656a482fb586ecdaa789ab235068043a7f85f SHA1: bd3b2114258a93dbd1108eaea341f8541ff74a47 MD5sum: 1f942f44319f70c9cc3afcaac2e70796 Description: data analysis framework for intra- and extra-cellular recordings This software aims to simplify data and analysis sharing for intra- and extra-cellular recordings. It supports time frequency plots, spike detection, spike rate calculation, and analysis of phase locked signals. . Data handling and storage utilizes a MySQL database, allowing to handle large amounts of data easily and efficiently. Therefore, a MySQL server running locally or on a remote machine is required. . This package provides the OpenElectrophy Python module. Python-Version: 2.4, 2.5 Package: python-scikits-learn Source: scikit-learn Version: 0.4-2~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 504 Depends: python (>= 2.5), python-support (>= 0.90.0), python-numpy, python-scipy, python-scikits-learn-lib (>= 0.4-2~squeeze.nd1) Recommends: python-nose, python-psyco, python-matplotlib Suggests: python-dap, python-scikits-optimization, python-scikits-learn-doc Provides: python2.5-scikits-learn, python2.6-scikits-learn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-scikits-learn_0.4-2~squeeze.nd1_all.deb Size: 123836 SHA256: ca4c763e20a52e609d0fd081e6548a24b22c64bb1d11badc868f48dadac4c62c SHA1: 398f9a7a23a6e01c57f9f9d248f8058d1ef5aa46 MD5sum: 3f31bab16ee3df536a22cdcfed0ac666 Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) Python-Version: 2.5, 2.6 Package: python-scikits-learn-doc Source: scikit-learn Version: 0.4-2~squeeze.nd1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 1132 Depends: libjs-jquery Suggests: python-scikits-learn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-scikits-learn-doc_0.4-2~squeeze.nd1_all.deb Size: 107988 SHA256: 5758a7b140ee75a4df0acd8acdcd3ba2eaeaf008f6dccd39221666d67a0418cf SHA1: 540d974936dcb1a957cdf083dd5b6cd822e1956f MD5sum: f514db5dd350424583e6def0f8de01c2 Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-scikits-learn. Package: python-scikits-learn-lib Source: scikit-learn Version: 0.4-2~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 920 Depends: libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), libsvm2, python (<< 2.7), python (>= 2.5), python-support (>= 0.90.0), python-numpy Provides: python2.5-scikits-learn-lib, python2.6-scikits-learn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-scikits-learn-lib_0.4-2~squeeze.nd1_i386.deb Size: 309738 SHA256: 196e98e09307f41d6d3a7cf2c2fdf03e4b55a764525d2db07f4bc88a6a3c17a1 SHA1: 04f6c38f794993c0b503de8c8b5b4f404a9796b8 MD5sum: 4dd336b54cbc7b670e4b930ecd6d5fea Description: low-level implementations and bindings for scikits-learn This is an add-on package for python-scikits-learn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Python-Version: 2.5, 2.6 Package: qlandkarte Source: qlandkartegt Version: 0.16.0-1~squeeze.nd1 Architecture: all Maintainer: Michael Hanke Installed-Size: 32 Depends: qlandkartegt Homepage: http://www.qlandkarte.org Priority: optional Section: x11 Filename: pool/main/q/qlandkartegt/qlandkarte_0.16.0-1~squeeze.nd1_all.deb Size: 2600 SHA256: 971cfe8965e2ac770ab91d1ff374cd8a75c9c59d21a4a3a6c2fec65f0aa36f27 SHA1: 94b85cfadc8414252933de2d0bab789f82ea1161 MD5sum: 461d6da351ea7fcd3dbffa8c5a5bfcf3 Description: Transitional package for QLandkarteGT This is a transitional package for the QLandkarte to QLandkarteGT upgrade, and can be safely removed after the installation is complete. Package: qlandkartegt Version: 0.16.0-1~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 4972 Depends: libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libgdal1-1.6.0, libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libproj0, libqt4-network (>= 4:4.5.3), libqt4-opengl (>= 4:4.5.3), libqt4-sql (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.5.3), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.1.1), libx11-6 Recommends: gdal-bin, qlandkartegt-garmin Replaces: qlandkarte Provides: qlandkarte Homepage: http://www.qlandkarte.org Priority: optional Section: x11 Filename: pool/main/q/qlandkartegt/qlandkartegt_0.16.0-1~squeeze.nd1_i386.deb Size: 2746470 SHA256: 051fe228305ff0cda9b7b33d57c4f1468f209b3936bcf7de4803b560b2627ef3 SHA1: 582f277bc81ca7f2c8e210a6d2607a0ad20b19fb MD5sum: afe54d1477816bc0fa3568f580f44ac8 Description: GPS mapping (GeoTiff and vector) and GPSr management This package provides a versatile tool for GPS maps in GeoTiff format as well as Garmin's img vector map format. QLandkarteGT is the successor of QLandkarte. Among various improvements (e.g. 2D/3D map rendering and reduced resource demands) the major difference is its device-independent architecture, which is not limited to Garmin devices anymore. Therefore, the package also does not include device drivers. Drivers for a number of Garmin devices are available from the qlandkartegt-garmin package. . Additionally, QLandkarteGT serves as a frontend to the GDAL tools, to make georeferencing of scanned maps feasible for users. In contrast to similar tools (e.g. QGis) its straightforward interface is especially suited for non-scientific users. Package: qlandkartegt-garmin Source: garmindev Version: 0.3.0-1~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 504 Depends: libc6 (>= 2.3.6-6~), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.2.1), libusb-0.1-4 (>= 2:0.1.12) Homepage: http://www.qlandkarte.org Priority: optional Section: utils Filename: pool/main/g/garmindev/qlandkartegt-garmin_0.3.0-1~squeeze.nd1_i386.deb Size: 173266 SHA256: 5accd56b9d821da2fad69ea72d98e85181f862f9243b23c86972a3dfacdd5411 SHA1: 6d08d975d38903b9a43b91a9f886d7258fd55363 MD5sum: 587a9221a1879465e1e74743385dcd0a Description: QLandkarteGT plugins to access Garmin devices A collection of plugins for QLandkarteGT to talk to various Garmin GPS devices, including GPSMap60CSx, GPSMap76, eTrexH, eTrexLegend and similar GPSr. Package: sigviewer Version: 0.3.0+svn362-1~pre1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 1424 Depends: libc6 (>= 2.7), libcholmod1.7.1 (>= 1:3.4.0), libfftw3-3, libgcc1 (>= 1:4.1.1), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.5.3), libstdc++6 (>= 4.4.0), zlib1g (>= 1:1.1.4) Homepage: http://sigviewer.sourceforge.net Priority: extra Section: science Filename: pool/main/s/sigviewer/sigviewer_0.3.0+svn362-1~pre1~squeeze.nd1_i386.deb Size: 598280 SHA256: cea623b789da1812e36c9f6df9546dbae47e7bf7c2adf5b6145d04e32b36a89e SHA1: a83597f289a23fddaa7bbba3a33dc8d03381e448 MD5sum: ce36192af8b5ef76aa686eb450bfd319 Description: GUI viewer for biosignals such as EEG, EMG, and ECG SigViewer is a viewing and scoring software for biomedical signal data. It relies on biosig4c++ library which supports a number of data formats (including EDF, BDF, GDF, BrainVision, BCI2000, CFWB, HL7aECG, SCP_ECG (EN1064), MFER, ACQ, CNT(Neuroscan), DEMG, EGI, EEG1100, FAMOS, SigmaPLpro, TMS32). The complete list of supported file formats is available at http://hci.tugraz.at/schloegl/biosig/TESTED . . Besides displaying biosignals, SigViewer supports creating annotations to select artifacts or specific events. Package: slicer Version: 3.4.0~svn10438-3~squeeze.nd1 Architecture: i386 Maintainer: Debian Science Team Installed-Size: 109832 Depends: libslicer3 (= 3.4.0~svn10438-3~squeeze.nd1), libc6 (>= 2.3.6-6~), libcurl3 (>= 7.16.2-1), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.1.1), libgdcm2.0 (>= 2.0.12), libgl1-mesa-glx | libgl1, libinsighttoolkit3.16, libkwwidgets1.0.0908, libopenigtlink1, libstdc++6 (>= 4.1.1), libvtk5.2, tcl8.5 (>= 8.5.0), vtk-tcl, slicer-data, itcl3, iwidgets4, tcllib, tcl8.5-kwwidgets Homepage: http://www.slicer.org/ Priority: optional Section: graphics Filename: pool/main/s/slicer/slicer_3.4.0~svn10438-3~squeeze.nd1_i386.deb Size: 23163276 SHA256: 3e91c2662ac069fb1f26d269b71e92d6eaa0e8def7cf4086050f1250fda6f956 SHA1: 0a064e6e4969b93b78fdafc57b705c4052c3e2e6 MD5sum: f9f144ec4df50bf71315b7fe9e7ab889 Description: software package for visualization and image analysis - main application Slicer is an application for computer scientists and clinical researchers. The platform provides functionality for segmentation, registration and three-dimensional visualization of multi-modal image data, as well as advanced image analysis algorithms for diffusion tensor imaging, functional magnetic resonance imaging and image-guided therapy. Standard image file formats are supported, and the application integrates interface capabilities to biomedical research software and image informatics frameworks. . 3D Slicer main application. Package: slicer-data Source: slicer Version: 3.4.0~svn10438-3~squeeze.nd1 Architecture: all Maintainer: Debian Science Team Installed-Size: 75656 Depends: tk8.5 | wish Homepage: http://www.slicer.org/ Priority: optional Section: doc Filename: pool/main/s/slicer/slicer-data_3.4.0~svn10438-3~squeeze.nd1_all.deb Size: 45850452 SHA256: c5a750d8b5ae619e7676d13bc9f8975e081771cfe9b6d534b000b54968903d3f SHA1: 34f83bdb09471100da1c6ea84b67a6064bf20708 MD5sum: 7470a7eb5cb992fb85799cd88960ff69 Description: software package for visualization and image analysis - share Slicer is an application for computer scientists and clinical researchers. The platform provides functionality for segmentation, registration and three-dimensional visualization of multi-modal image data, as well as advanced image analysis algorithms for diffusion tensor imaging, functional magnetic resonance imaging and image-guided therapy. Standard image file formats are supported, and the application integrates interface capabilities to biomedical research software and image informatics frameworks. . 3D Slicer data files. Package: svgtune Version: 0.1.0-1~squeeze.nd1 Architecture: all Maintainer: Yaroslav Halchenko Installed-Size: 64 Depends: python, python-lxml Suggests: inkscape Homepage: http://github.com/yarikoptic/svgtune Priority: optional Section: graphics Filename: pool/main/s/svgtune/svgtune_0.1.0-1~squeeze.nd1_all.deb Size: 6762 SHA256: dfb3f87538fbcda51f3aca8078e68fe2855d8ef8766db814f11c9dfd9119a012 SHA1: 43ff190059a2ef774bf5600cd15d46820ac17260 MD5sum: 51f3db6a86e9a28de3bbd0b281063186 Description: tool to generate a set of .svg files out of a single .svg file svgtune is just a little helper to generate a set of .svg files out of a single .svg file, by tuning respective groups/layers visibility, transparency or anything else. . It might come very handy for generation of incremental figures to be embedded into the presentation in any format which inkscape could render using original .svg file (e.g. pdf, png). Package: via-bin Source: via Version: 1.6.0-2~squeeze.nd1 Architecture: i386 Maintainer: Michael Hanke Installed-Size: 828 Depends: lesstif2 (>= 1:0.94.4), libblas3gf | libblas.so.3gf | libatlas3gf-base, libc6 (>= 2.3), libgsl0ldbl (>= 1.9), libice6 (>= 1:1.0.0), libpng12-0 (>= 1.2.13-4), libsm6, libvia0, libx11-6, libxext6, libxmu6, libxt6 Homepage: http://www.cbs.mpg.de/institute/software/lipsia Priority: optional Section: libs Filename: pool/main/v/via/via-bin_1.6.0-2~squeeze.nd1_i386.deb Size: 174850 SHA256: e11e9d7aa657e76f4728f90affb75ec9da7af2bfad08f4db2b9beeaf2e23fde8 SHA1: e4fd24a57e867c43e1a1a2ed1facb0e658bdec23 MD5sum: a7b674b69bdca403db243833a0c01526 Description: tools for volumetric image analysis VIA is a volumetric image analysis suite for functional and structural (medical) images. The suite consists of different tools ranging from simple data handling over viewers to complex image transformation. . All tools operate on data in VISTA format. The package contains several converters from e.g. PNG, PGM or PNM to this data format and back. Package: voxbo Version: 1.8.5~svn1172-1~squeeze.nd1 Architecture: i386 Maintainer: NeuroDebian Team Installed-Size: 9160 Depends: libc6 (>= 2.3.6-6~), libfontconfig1 (>= 2.8.0), libgcc1 (>= 1:4.1.1), libgsl0ldbl (>= 1.9), libpng12-0 (>= 1.2.13-4), libqt4-network (>= 4:4.5.3), libqt4-qt3support (>= 4:4.5.3), libqtcore4 (>= 4:4.6.1), libqtgui4 (>= 4:4.6.1), libstdc++6 (>= 4.4.0), libx11-6, libxext6, libxi6, libxrender1, zlib1g (>= 1:1.1.4) Suggests: mni-colin27-nifti Homepage: http://www.voxbo.org Priority: extra Section: science Filename: pool/main/v/voxbo/voxbo_1.8.5~svn1172-1~squeeze.nd1_i386.deb Size: 3517362 SHA256: a47ebc59fa1a35443d218afbe8353b6bb5b38ab412edb98dea90ddb9d59e8bbe SHA1: 420c34d9e90b04b04a7283c19919b6c5d237068c MD5sum: 0809ca7179a3e8fdf7d5fcbad39bec4a Description: processing, statistical analysis, and display of brain imaging data This is a toolkit for analysis of functional neuroimaging (chiefly fMRI) experiments and voxel-based lesion-behavior mapping. VoxBo supports the modified GLM (for autocorrelated data), as well as the standard GLM for non-autocorrelated data. The toolkit is designed to be interoperable with AFNI, FSL, SPM and others.