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A Machine Learning Approach to Elasticity Imaging

A Machine Learning Approach to Elasticity Imaging [1]

Professor Insana from the University of Illinois at Urbana-Champaign has developed an information based technique to determine the mechanical properties of soft biological media. This technique has been adapted from the Auto-progressive algorithm that was originally developed for civil engineering applications. This algorithm is a unique combination of Force Displacement, Finite Element Algorithm (FEA), and Artificial Neural Network (ANN) along with what to sample and where to look. It is better than the inverse analysis or dynamic imaging techniques in that it has a machine learning aspect which eliminates the need of making any initial assumptions about the media being imaged. The technology has a lot of potential in non-linear imaging and is not tied to any one particular type of imaging technique. Its primary application is in ultrasound imaging.

Michael
Insana

Inventors:

Michael Insana
The Office of Technology Management
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Source URL:https://otm.illinois.edu/technologies/machine-learning-approach-elasticity-imaging

Links
[1] https://otm.illinois.edu/technologies/machine-learning-approach-elasticity-imaging