Accurate optical flow field estimation using mechanical properties of soft tissues

A novel optical flow based technique is presented in this paper to measure the nodal displacements of soft tissue undergoing large deformations. In hyperelasticity imaging, soft tissues maybe compressed extensively [1] and the deformation may exceed the number of pixels ordinary optical flow approaches can detect. Furthermore in most biomedical applications there is a large amount of image information that represent the geometry of the tissue and the number of tissue types present in the organ of interest. Such information is often ignored in applications such as image registration. In this work we incorporate the information pertaining to soft tissue mechanical behavior (Neo-Hookean hyperelastic model is used here) in addition to the tissue geometry before compression into a hierarchical Horn-Schunck optical flow method to overcome this large deformation detection weakness. Applying the proposed method to a phantom using several compression levels proved that it yields reasonably accurate displacement fields. Estimated displacement results of this phantom study obtained for displacement fields of 85 pixels/frame and 127 pixels/frame are reported and discussed in this paper.