This paper presents a level set based segmentation method with shape priors. The shape priors guide the level set deformations so that the contour extraction process is affected not only from the local image properties, but also from the expert knowledge in the form of manual contours. The method does not need an explicit training phase and it does not complicate the level set functional because level set deformations and incorporation of prior information are done separately. The system uses manual expert contours to produce new level set surfaces which are warped into the surface from the level set process. The prior information is incorporated into the level sets by re-initializing these warped surfaces as new level set surfaces. The resulting system is validated by running experiments on synthetic data and real MR and ultrasound cardiac images.