A method has been developed for estimating elasticity and boundary forces automatically using an iterative optimization framework, given the desired (target) output surface. During the optimization, the input model is deformed by a simulator, and an objective function based on some error metrics (e.g. distance, landmarks, etc.) between the deformed surface and the target surface is minimized numerically. The optimization framework does not depend on a particular simulation method and is therefore suitable for different physical models. The method is commercially viable because estimation of tissue stiffness is an important means of non-invasive cancer detection and staging. Existing elasticity reconstruction methods usually depend on a dense displacement field and known external forces. Many imaging modalities, however, cannot provide details within an organ and therefore cannot provide such a displacement field. Furthermore, force exertion and measurement can be difficult for some internal organs, making boundary forces another missing parameter.
• The method estimates elasticity in several different physical models
• Based on preliminary results, recovered elasticity values using this method had a significant positive correlation with clinical prostate cancer staging
- Simulation-Based Joint Estimation of Body Deformation and Elasticity Parameters for Medical Image Analysis IEEE Xplore Digital Library 08 August 2012 10.1109/TMI.2012.2212450