Stephan Gerhard
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Stephan Gerhard has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Alessandro Daducci
Department of Computer Science, University of Verona, Verona, Italy
1 shared publication Alia Lemkaddem
Signal Processing Laboratory 5, Ecole Polytechnique Fédérale de Lausanne Lausanne, Switzerland
1 shared publicationJean-Philippe Thiran
Signal Processing Laboratory 5, Ecole Polytechnique Fédérale de Lausanne Lausanne, Switzerland
1 shared publicationPatric Hagmann
Department of Radiology, University Hospital Center and University of Lausanne Lausanne, Switzerland
1 shared publicationReto Meuli
Department of Radiology, University Hospital Center and University of Lausanne Lausanne, Switzerland
1 shared publication
Latest Publications
- Open Access
- 1 January 2011
- Published by Frontiers Media SA in Frontiers in Neuroinformatics
- Vol. 5, 10144
The Connectome Viewer Toolkit: An Open Source Framework to Manage, Analyze, and Visualize Connectomes
Advanced neuroinformatics tools are required for methods of connectome mapping, analysis and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration and sharing. We have designed and implemented the Connectome Viewer Toolkit --- a set of free and extensible open-source neuroimaging tools written in Python. The key components of the toolkit are as follows: 1. The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. 2. The Connectome File Format Library enables management and sharing of connectome files. 3. The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer's plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/.
- 1 January 2011
- Published by Frontiers Media SA in Frontiers in Neuroinformatics
- Vol. 5, 10144
Open AccessThe Connectome Viewer Toolkit: An Open Source Framework to Manage, Analyze, and Visualize Connectomes
Advanced neuroinformatics tools are required for methods of connectome mapping, analysis and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration and sharing. We have designed and implemented the Connectome Viewer Toolkit --- a set of free and extensible open-source neuroimaging tools written in Python. The key components of the toolkit are as follows: 1. The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. 2. The Connectome File Format Library enables management and sharing of connectome files. 3. The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer's plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/.