Soft Tissue Characterization Using Genetic Algorithm

Soft tissue properties are important to many modern applications of technology to medicine, such as robotic surgery, soft tissue modeling, and surgical simulation with force feedback. However, realistic acquisition of soft tissue properties is extremely challenging, not only because of the nonlinearity, anisotropy, nonhomogeneity, rate dependence, and time dependence of soft tissues but also due to the layered and nonhomogeneous structures of soft tissues [Samur et al. 2007; Kim et al. 2008; Zhong et al. 2010, 2012]. It is understood that soft tissue properties may dynamically change during the surgical process according to different patients, different organs, different functional regions and layers crossed by the surgical tools, and different physiological conditions. Therefore, it requires that mechanical properties of soft tissues be acquired and studied through a real-time intraoperative.