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  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.
Most conventional methods of breast cancer diagnosis such as X-ray, Ultrasound (US) and MRI have some issues
ranging from weaknesses associated with tumour detection or classification to high cost. In this study, we propose a
breast elastography technique based on 3D US. This technique is fast, expected to be cost effective and more sensitive
and specific compared to US imaging. Unlike current elastography techniques that image relative elastic modulus, this
technique is capable of imaging absolute Young's modulus (YM). In this technique, tissue displacements and surface
forces used to mechanically stimulate the tissue are acquired and used as input to reconstruct the tissue YM distribution.
For the displacements acquisition, we use a modified optical flow technique to estimate the displacement of each node
from 3D US pre- and post-compression images. A force sensor is used to measure forces on the surface of the breast.
These forces are input into an analytical model to estimate tissue stress distribution. By combining the stress field with
the strain field calculated from the estimated displacements using Hooke's law, the YM can be reconstructed efficiently.
Also, we adapted a micromechanics based model developed for strain distribution estimation in heterogeneous medium
to update the reconstructed YM value of tumor more accurately.