Tissue identification using inverse finite element analysis of rolling indentation

The authors have recently proposed the method of rolling indentation over soft tissue to rapidly identify soft tissue properties for localization and detection of tissue abnormalities, with the aim of compensating for the loss of haptics information experienced during robotic-assisted minimally invasive surgery (RMIS). This paper investigates the concept of rolling indentation using Finite Element modeling. To obtain ground truth data, rolling indentation experiments are conducted on a silicone phantom which contains three simulated tumours. The tissue phantom is modeled as hyperelastic material using ABAQUS^TM. The identification of tumours includes two parts: firstly, when the spatial location of tumour is known, identify the tumour's mechanical properties (initial shear modulus); secondly if the mechanical properties of tumour are known, identify the tumour's spatial location. The results show that the proposed method can identify information of tumours accurately and robustly. The identified tumour mechanical properties and tumour locations are in good agreement with experimental measurements.