Aurelien F. Stalder1, Mehmet Akif Gulsun2, Andreas Greiser3, Marie-Pierre Jolly2
1Siemens AG - Healthcare, Erlangen, Germany; 2Imaging and computer vision, Siemens Corporation - Corporate Technology, Princeton, NJ, United States; 3Siemens AG, Erlangen, Germany
Segmentation, analysis and visualization of 4D Flow data often requires manual interaction and can be complex and time-consuming. In order to overcome the complexity of the processing of such data, a fully automatic approach for visualization of 4D Flow data is presented. Based on the assumption that 4D Flow data can be classified in three kinds of regions: air/lungs, static tissues and vessels/ventricles a data clustering technique is first applied to robustly detect flow regions. Then particle traces are seeded everywhere in the flow region so as to produce fully-automatic 4D visualization of flow data.