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Guoyan Zheng, PhD, PD: 3D Personalized Reconstruction of External Shape and Internal Intensity Distribution from X-ray Images: Statistical Model-based Solutions
06.08.2012 Berliner Colloquium für wissenschaftliche Visualisierung
Guoyan Zheng, PhD, PD
Institute for Surgical Technology and Biomechanics, University of Bern
3D Personalized Reconstruction of External Shape and Internal Intensity Distribution from X-ray Images: Statistical Model-based Solutions
The applications of two-dimensional (2D) X-ray imaging in orthopedics are pervasive, both pre-operatively and intra-operatively. However, due to the projective character of 2D X-ray imaging, the accuracy of an X-ray image based application is restricted. One way to address this limitation is to learn a statistical model and to adapt the learned model to the patient’s individual anatomy based on a limited number of calibrated X-ray images. The reconstructed model can then provide detailed 3D information for the considered anatomical structure. In this talk, I will present various solutions that have been developed in my team for reconstructing 3D personalized external shape and internal intensity distribution. I will start with a solution that can reconstruct the external shape of an anatomical structure with none or mild degree of pathology even when a statistical model learned from a normal population is used. In order to apply 2D/3D reconstruction to an intra-operative application, we developed a fully automatic solution, combining particle filtering based morphological parameter detection, loopy belief propagation based contour extraction, and statistical shape model based 2D/3D registration. Our more recent work focuses on reconstructing not only the external shape but also the internal intensity distribution. Applications of our solutions are pre-operative planning, intraoperative surgical intervention, and post-operative treatment evaluation.
Monday, August 6, 2012, 17:15 Uhr
Zuse-Institut Berlin, Takustraße 7, 14195 Berlin
Lecture Hall (rotunda, ground floor)
M. Alexa (TUB), J. Döllner (HPI), P. Eisert (HUB), H.-C. Hege (ZIB), K. Polthier (FUB), J. Sullivan (TUB)