Computer Graphics and Visualization • Publications

IEEE Transactions on Visualization and Computer Graphics

Automatic Detection and Visualization of Qualitative Hemodynamic Characteristics in Cerebral Aneurysms

R. Gasteiger, D. Lehmann, R.F.P. van Pelt, G. Janiga, O. Beuing, Anna Vilanova, H. Theisel, and Bernhard Preim

Overview of the extraction approach: Based on the flow grid and the aneurysm ostium we seed streamlines at the ostium into the aneurysm. We identify several local line properties on the streamlines to compute a quality scalar field on the ostium. Given this scalar field we extract a seeding curve on the ostium, which is used to construct the boundary contour of the inflow jet. A second scalar field is computed on the aneurysm surface to indicate the impingement zone. Finally, we visualize both information expressively.

Cerebral aneurysms are a pathological vessel dilatation that bear a high risk of rupture. For the understanding and evaluation of the risk of rupture, the analysis of hemodynamic information plays an important role. Besides quantitative hemodynamic information, also qualitative flow characteristics, e.g., the inflow jet and impingement zone are correlated with the risk of rupture. However, the assessment of these two characteristics is currently based on an interactive visual investigation of the flow field, obtained by computational fluid dynamics (CFD) or blood flow measurements. We present an automatic and robust detection as well as an expressive visualization of these characteristics. The detection can be used to support a comparison, e.g., of simulation results reflecting different treatment options. Our approach utilizes local streamline properties to formalize the inflow jet and impingement zone. We extract a characteristic seeding curve on the ostium, on which an inflow jet boundary contour is constructed. Based on this boundary contour we identify the impingement zone. Furthermore, we present several visualization techniques to depict both characteristics expressively. Thereby, we consider accuracy and robustness of the extracted characteristics, minimal visual clutter and occlusions. An evaluation with six domain experts confirms that our approach detects both hemodynamic characteristics reasonably.

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Citation

R. Gasteiger, D. Lehmann, R.F.P. van Pelt, G. Janiga, O. Beuing, Anna Vilanova, H. Theisel, and Bernhard Preim, Automatic Detection and Visualization of Qualitative Hemodynamic Characteristics in Cerebral Aneurysms, IEEE Transactions on Visualization and Computer Graphics, 18, pp. 2178–2187, 2012.

BibTex

@article{bib:gasteiger:2012,
    author       = { Gasteiger, R. and Lehmann, D. and van Pelt, R.F.P. and Janiga, G. and Beuing, O. and Vilanova, Anna and Theisel, H. and Preim, Bernhard },    
    title        = { Automatic Detection and Visualization of Qualitative Hemodynamic Characteristics in Cerebral Aneurysms },
    journal      = { IEEE Transactions on Visualization and Computer Graphics },
    volume       = { 18 },
    year         = { 2012 },
    pages        = { 2178--2187 },
    doi          = { 10.1109/TVCG.2012.202 },
    dblp         = { journals/tvcg/GasteigerLPJBVTP12 },
    url          = { https://publications.graphics.tudelft.nl/papers/283 },
}