Physical model based recovery of displacement and deformations from 3D medical images

Estimating tissue displacement and deformation from time-varying medical images is a common problem in biomedical image analysis. For example, in order to better manage patients with ischemic heart disease, it would be useful to know their current extent of injury. This can be assessed by accurately tracking the motion of the left ventricle of the beating heart. Another example of this type of application is estimating the displacement of brain tissue during neurosurgery. The latter application is necessary because the presurgical planning for these delicate surgeries is based on images that may not accurately reflect the intraopertave brain (due to the action of gravity and other forces). In both examples, the tissue deformation cannot be measured directly. Instead, a sparse set of (potentially noisy) displacement estimates are extracted from acquired images. In this chapter, we explain how to use the physical properties of underlying organs or structures to guide such estimations of deformation, using neurosurgery and cardiac motion as example cases.