Fuzzy Estimation of Liver Stiffness in Modelling Liver Deformation

The skill of a successful operation requires a thorough understanding on the particular organs, perhaps de facto surgery is complex nowadays. Therefore, surgical simulator has become an alternative demanding tool among the surgeons to practice and conducting pre-operation planning. Due to the ease of implementation of Mass Spring Model (MSM), the context of MSM has been extended to real-time invasive surgical simulator. However, the remaining drawback of MSM is the selection of parameter -- stiffness. In this research, the fuzzy knowledge based system is introduced into the MSM. We present an improved MSM to simulate the liver deformation for surgery simulation. The underlying MSM is redesigned where the parameters are determined by using knowledge-based fuzzy logic. Comparison between different fuzzy approaches such as Interval Type-2 Fuzzy Sets (IT2), Mamdani and Sugeno are made. Among the three fuzzy approaches, IT2 has the highest similarity with the benchmark model. The stiffness values estimated by fuzzy approaches are in very good agreement with the benchmark result as each of the respective fuzzy approach graphs share the similar trend of displacement and velocity with the benchmark model.