Modules:VMTKSlicerModule

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Module Name

VmtkSlicerModule

General Information

Module Type & Category

Type: GUI-less loadable module

Category: Extension

Authors, Collaborators & Contact

• Author: Daniel Haehn, University of Heidelberg
• Supervisor: Luca Antiga, Mario Negri Institute
• Contact: Daniel Haehn, haehn@bwh.harvard.edu

Module Description

This GUI-less loadable module provides the libraries of the Vascular Modeling Toolkit (http://www.vmtk.org/) in 3D Slicer.

It is part of the NA-MIC VMTK Collaboration.

Official project page: http://www.vmtk.org/Main/VmtkIn3DSlicer

Usage and Installation

TODO manual install TODO extension

Examples, Use Cases & Tutorials

After installing the library, the following Python scripted modules can be installed and used.

VMTKLevelSetSegmentation - providing level-set segmentation of vessels, aneurysms and tubular structures using different algorithms

VMTKVesselEnhancement - providing vessel enhancement filters to highlight vasculature or tubular structures

Development

Source code & Documentation

The complete source code is available at a NITRC SVN repository.

The most important files are the following:

• CMakeLists.txt to include the vtkVmtk libraries during compilation

• vtkVmtkSlicerModuleLogic.cxx to initialize the generated Tcl wrapper classes of the vtkVmtk libraries

Since the Tcl initialization is performed, the vtkVmtk library can also be accessed from Python in 3D Slicer.

Information and documentation concerning the integration of VMTK can be found in this student research project write-up.

Known bugs

Follow this link to the VMTK in 3D Slicer bug tracker.

More Information

Acknowledgment

This work was funded by a charitable grant of the Thomas­-Gessmann Foundation part of the Founder Federation for German Science.

References

• Piccinelli M, Veneziani A, Steinman DA, Remuzzi A, Antiga L (2009) A framework for geometric analysis of vascular structures: applications to cerebral aneurysms. IEEE Trans Med Imaging. In press.
• Antiga L, Piccinelli M, Botti L, Ene-Iordache B, Remuzzi A and Steinman DA. An image-based modeling framework for patient-specific computational hemodynamics. Medical and Biological Engineering and Computing, 46: 1097-1112, Nov 2008.