Modelling palpable masses for a virtual breast examination.

In this paper we work towards developing a palpation simulator to train the early detection of breast cancer. In order to achieve this we formulate a virtual model that accurately captures the influence of a tumour embedded in breast tissue, on the skin surface. Enhancing the skills involved in breast examination is important for clinicians in healthcare and also for the general public. A haptic interface facilitates the transfer of tactile information to the user enabling lump detection. This is driven by a deformable model constructed using a mass spring system. However there are issues when simulating inhomogeneous compositions of tissue using this approach. In this research we are predominantly interested in modelling the relationship between the surface and non-spherical cancers accurately, whilst permitting reconfiguration and adhering to the material properties of soft tissues. Evaluations performed against finite element models and varying geometries demonstrate an accurate response. The novelty of our approach means that the presence of a tumour can be perceived on the surface, in the absence of volumetric meshing, thus speeding up interactivity.