Effective mesh smoothing for haptic rendering in medical applications

Mesh models can be extracted from medical imaging data. However some methods (e.g., CT) may suffer from severe artifacts (e.g., staircases, noises) in current clinical routine. As a consequence, haptic systems, when using these influenced mesh models, will become unstable. To tackle this problem, in this paper we propose an effective medical-oriented smoothing algorithm focusing on haptic rendering. Our algorithm mainly consists of two stages, namely vertex re-sampling and surface fitting. The first stage is adopted to eliminate staircases while the second can obtain the underlying surface by least square fitting method. Experiments on various medical imaging data present the efficacy of our methodology, which can achieve higher quality results than previous approaches regarding both surface smoothness and surface accuracy. And the final results on haptic applications further show this proposed technique is suitable for medical surgery simulations.