Registering 3D Lung Surfaces Using the Shape Context Approach∗

Studying the complex thorax breathing motion is an important research topic for medical (e.g. fusion of function and anatomy, radiotherapy planning) and engineering (reduction of motion artifacts) questions. In this paper we present first results on studying the 4D motion of segmented lung surfaces from CT scans at several different breathing states. For this registration task we extend the shape context approach for shape matching by Belongie et al. [1] from 2D shapes to 3D surfaces and apply it to segmented lung surfaces. Resulting point correspondences are used for a non-rigid thin-plate-spline registration. We describe our experiments on synthetic and real thorax data and show our quantitative and qualitative results.