Monday, August 6, 2012 - 17:15

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)