Automated volume sampling optimization for direct volume deformation in patient-specific surgical simulation

Patient-specific, interactive surgical simulation has become a major research direction in the biomedical side of computer graphics. While performing deformation on patients' medical volume data provides a realistic venue to define the most suitable operative strategy, the current simulators rely heavily on human efforts for data preprocessing. Such manual procedures not only require special knowledge from the users, they are tedious and time-consuming. This paper presents a novel volume sampling approach for preoperative planning by automating various conventional data preprocessing procedures. The optimization method is capable of adapting to any volume data and supports heterogeneous tissue characterization such that anatomical surroundings deform together with the deforming organ. In this way, physicians' user experience in surgical manipulation will be greatly improved. Results of the experiments suggested that the presented segmentation-free and modeling-free method is a more efficient and practical approach to interactive medical simulation.