On modal modeling for medical images: underconstrained shape description and data compression
S. Sclaroff, Alex Pentland · 2002
The authors have previously described modal analysis, an efficient, physically-based solution for recovering, tracking, and recognizing solid models from 2D and 3D sensor data. The underlying representation consists of two levels: modal deformations, which describe the overall shape of a solid, and displacement maps, which employ a multiscale wavelet representation to provide local and fine surface detail. Here, the authors address the problem of recovering modal models in the underconstrained case of fitting a 3D model to contours found in medical slice and X-ray data. They describe an extension which can be used to incorporate measurement uncertainty while estimating the modal deformation parameters. Finally, the authors give details about how to compress dense 3D point data from surfaces, by use of displacement maps and wavelets.>