The sliding motion between two anatomic structures, such as lung against chest wall and liver against surrounding tissues, produces a discontinuous displacement field between their boundaries. Capturing the sliding motion is quite challenging for intensity-based image registration methods in which a smoothness condition has commonly been applied to ensure the deformation consistency of neighborhoodvoxels. Although biomechanical models could explicitly model the discontinuity, their accuracy in recovering deformation fields of inner tissue structures is limited due to the difficulty of incorporating the intensity information of inner tissue structures into the models.
To tackle this problem, we have developed a new biomechanical model based image registration framework. It incorporates a patient-specific biomechanical model with a non-rigid image registration scheme for motion estimation of sliding objects. The patient-specific model provides the motion estimation with an explicit simulation of sliding motion, while the subsequent non-rigid image registration compensates for smaller residuals of the deformation due to the inaccuracy of the physical model. In this talk, I will present three applications of the proposed method: lung motion estimation for radiotherapy, liver motion estimation for HIFU treatment and alignment of prone and supine MR breast images for breast surgery.