Raffaele Ponzini, HPC group, CILEA, Segrate (MI), Italy
Alice Invernizzi, HPC group, CILEA, Segrate (MI), Italy
Francesco Iannaccone, biommeda, Ibitech , Ghent University, Belgium
Giovanna Rizzo, IBFM-CNR, Milan, Italy
Visualization and computing of hemodynamic data is becoming a common challenge in medical imaging since there is an increasing amount of multidimensional flow-related clinical data produced by means of evolving technologies such as Phase Contrast MRI. In this context, there is a strong need for software that can deal with multi-dimensional (spatial and temporal) flow data allowing to fully exploit the insight contained in the data [1,2].
In this work we propose a novel Graphic User Interface (GUI) application fully written in Python and designed using open source libraries (Visualization Toolkit , numpy , scipy , pyQT ) that aims at helping researchers and clinicians to visualize and process 4D hemodynamics data (3D along time) in a more effective way.
Thanks to this novel application we show how it is possible to visualize both anatomical and hemodynamics quantities (vectors, stream-lines, streak-lines, contours, iso-surfaces) distinguishing the three velocity encoding axis and allowing the interplay of both 3D view and radiological reference planes at the same times in order to enhance flow characteristics and therefore improving the understanding of such complex phenomena.
1. Toussaint N et al. Eurographics Workshop on Visual Computing for Biomedicine, 2008.
2. Roy van Pelt et al. IEEE Transactions on Visualization and Computer Graphics, 2010.
3. VTK project: http://www.vtk.org/
4. Numpy project: http://numpy.scipy.org/
5. Scipy project: http://www.scipy.org/
6. QT product: http://qt.nokia.com/products/