Nonrigid registration with adaptive content-based filtering of the deformation field

In present-day medical practice it is often necessary to nonrigidly align image data, either intra- or inter-patient. Current registration algorithms usually do not take different tissue types into account. A problem that might occur with these algorithms is that rigid tissue, like bone, also deforms elastically. We propose a method to correct a deformation field, that is calculated with a nonrigid registration algorithm. The correction is based on a second feature image, which represents the tissue stiffness. The amount of smoothing of the deformation field is related to this stiffness coefficient. By filtering the deformation field on rigid tissue, the deformation field will represent a local rigid transformation. Other parts of the image containing nonrigid tissue are smoothed less, which leaves the original elastic deformation (almost) untouched. It is shown on a synthetic example and on inspiration-expiration CT data of the thorax, that a filtering of the deformation field based on tissue type indeed keeps rigid tissue rigid, thus improving the registration results.