Nutonian Piercing the Veil of Distortion Over Mission-Critical Images

Posted by Jay Schuren

12.08.2014 10:00 AM

Screen_Shot_2014-08-08_at_2.36.47_PMImaging and advanced characterization are at the heart of a range of industries across aircraft component inspections, medical imaging, CPU manufacturing and more. As society continues to push the envelope in technological innovation, demand for the best quantitative characterization possible is always present. Distortion, or warping of image data, arises from the imaging equipment itself; common examples are fish eye lenses or fun house mirrors. A little-discussed issue is that changing the instrument settings often changes the distortion – limiting peak characterization performance across fields, reducing accuracy and escalating time and effort for discovery.

The majority of the innovation in imaging systems has been focused on showing ever-smaller features. But those expensive high-magnification machines still have distortion issues that no one has addressed. Inspired by work with the Air Force Research Laboratory, Nutonian has developed tools able to dynamically eliminate image distortion. Applying Nutonian’s data science automation engine, Eureqa, allows users to rapidly identify specific relationships between the instrument settings/environmental conditions and the limiting distortions.


Now, instead of pretending that image distortion either doesn’t exist or remains static across different instrument settings, companies can computationally model, predict and calculate behavior at a high degree of accuracy based on the measurements they take from an image. Understanding these causal relationships gives users the ability to “unwarp” image distortions, enabling accurate insight and peak performance when it really matters. The implications could mean saved lives and >10x improvements in quantitative measurements for systems such as Scanning Electronic Microscopes, realizing peak performance even in outdated equipment.

Whether companies are looking for cracks in aircraft turbine blades or tumors in a mammogram, current limits of characterization systems govern the status quo for early identification. Applying Eureqa to a Scanning Electron Microscope and a mammography detector over a range of conditions resulted in >10x improvements in quantitative measurements. Gain competitive advantage with access to improved detection systems that will save lives, reduce costs and accelerate the development of next generation products.

Topics: Advanced Techniques, Big data, Case study, nutonian, U.S. Air Force

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