Haptic landmark positioning and automatic landmark transfer in 4D Lung CT data

Abstract

Manual landmark positioning in volumetric image data is a complex task and often results in erroneous landmark positions. The landmark positioning tool presented uses image curvature features to precompute suitable candidates for landmark positions on surface data of anatomical structures. A force-feedback I/O device is then used to haptically guide the user during the definition of the correct landmarks in the 3D data volume. Furthermore, existing landmarks in a time-point of a sequence of 3D volumes (4D data set) can iteratively be transferred to other time-points using a surface based registration technique. First results show significant time savings and small interobserver variability (IROV) compared to the IROV of manually defined landmark positions using orthogonal slices of the image data.