Biomechanical Imaging is an emerging and exciting suite of medical imaging techniques. The goal of biomechanical imaging is to map the mechanical properties, for example Young’s modulus, of soft tissues. Physician’s find elastography very appealing, in as much as it provides a visual and quantitative representation of what they are trained to detect with their finger tips. Furthermore, it has the potential to see smaller, deeper and softer inclusions than might be detectable by touch. Medical researchers have identified a myriad of potential applications for elastography, including the diagnosis and treatment of deep vein thrombosis, breast, prostate and liver cancers, local and diffuse coronary disease, fibrosis, edema and cirrhosis. Miniaturization technology allows much of this to be accomplished with an ultrasound scanner that costs about as much as a mid-priced car. (Imagine every GP’s office in the U.S. with it’s own ultrasound scanner.) For all of these and several other reasons, biomechanical imaging is a very exciting and rapidly growing area in medical imaging.

A key step in biomechanical imaging is the ability to measure soft tissue deformation in vivo. To accomplish this, we image the tissue while it is being deformed and through image registration techniques, extract the deformation from the image sequence. The required registration accuracy is intimidating: pixel displacements of few millimeters need to be measured with a precision of a few microns. This talk will review the mathematics and computational issues underlying some “standard” motion extraction techniques to accomplish these goals, and some new techniques developed by our team.

Acknowledgements: Assad Oberai and the B.U. Biomechanical Imaging Team, Nachiket Gokhale, Mike Richards, Lindsey Nelson, Carlos Rivas and Ricardo Leiderman. Funding form DOD, CDMRP, BCRP and CenSSIS.

Page last updated 07/10/2006. Please send comments to Cheryl Endicott