naa a22 4500 510808271 CHVBK 20180411083428.0 cr unu---uuuuu 180411e20130301xx s 000 0 eng 10.1007/s11548-012-0779-1 doi (NATIONALLICENCE)springer-10.1007/s11548-012-0779-1 Automatic generation of anatomic characteristics from cerebral aneurysm surface models [Elektronische Daten] [M. Neugebauer, K. Lawonn, O. Beuing, B. Preim] Purpose: Computer-aided research on cerebral aneurysms often depends on a polygonal mesh representation of the vessel lumen. To support a differentiated, anatomy-aware analysis, it is necessary to derive anatomic descriptors from the surface model. We present an approach on automatic decomposition of the adjacent vessels into near- and far-vessel regions and computation of the axial plane. We also exemplarily present two applications of the geometric descriptors: automatic computation of a unique vessel order and automatic viewpoint selection. Methods: Approximation methods are employed to analyze vessel cross-sections and the vessel area profile along the centerline. The resulting transition zones between near- and far- vessel regions are used as input for an optimization process to compute the axial plane. The unique vessel order is defined via projection into the plane space of the axial plane. The viewing direction for the automatic viewpoint selection is derived from the normal vector of the axial plane. Results: The approach was successfully applied to representative data sets exhibiting a broad variability with respect to the configuration of their adjacent vessels. A robustness analysis showed that the automatic decomposition is stable against noise. A survey with 4 medical experts showed a broad agreement with the automatically defined transition zones. Conclusion: Due to the general nature of the underlying algorithms, this approach is applicable to most of the likely aneurysm configurations in the cerebral vasculature. Additional geometric information obtained during automatic decomposition can support correction in case the automatic approach fails. The resulting descriptors can be used for various applications in the field of visualization, exploration and analysis of cerebral aneurysms. CARS, 2012 Cerebral aneurysm nationallicence Decomposition nationallicence Automatic characterization nationallicence Anatomic descriptors nationallicence Neugebauer M. Department of Simulation and Graphics, University of Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany aut Lawonn K. Department of Simulation and Graphics, University of Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany aut Beuing O. Department of Neuroradiology, University Hospital Magdeburg, Magdeburg, Germany aut Preim B. Department of Simulation and Graphics, University of Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany aut International Journal of Computer Assisted Radiology and Surgery Springer-Verlag 8/2(2013-03-01), 279-289 1861-6410 8:2<279 2013 8 11548 https://doi.org/10.1007/s11548-012-0779-1 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11548-012-0779-1 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Neugebauer M. Department of Simulation and Graphics, University of Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany aut NATIONALLICENCE 700 1- Lawonn K. Department of Simulation and Graphics, University of Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany aut NATIONALLICENCE 700 1- Beuing O. Department of Neuroradiology, University Hospital Magdeburg, Magdeburg, Germany aut NATIONALLICENCE 700 1- Preim B. Department of Simulation and Graphics, University of Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany aut NATIONALLICENCE 773 0- International Journal of Computer Assisted Radiology and Surgery Springer-Verlag 8/2(2013-03-01), 279-289 1861-6410 8:2<279 2013 8 11548 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer