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WARF: P120292US01

Confidence Maps for MRI Parametric Mapping


INVENTORS -

Scott Reeder, Diego Hernando Arribas

The Wisconsin Alumni Research Foundation (WARF) is seeking commercial partners interested in developing a method for identifying and avoiding sources of error in parametric maps.
OVERVIEWMagnetic resonance parametric mapping is a general framework for measuring important biomarkers. In the process, several images from the same field of view are obtained using different acquisition parameters (echo time, repetition time, encoding gradients, etc.). These different parameters help produce images in which contrast varies in a controlled way. For example, in chemical-shift encoded imaging, several images are acquired with different echo times, giving rise to different relative phases between chemical species. The map of a desired parameter is produced from the image series.

However, the process can be degraded by image artifacts and noise, which introduce systematic errors in certain areas of the parametric maps. Identifying these unreliable regions would enable cleaner maps.
THE INVENTIONUW–Madison researchers have developed a method for reducing parametric mapping errors using ‘confidence maps’ that identify problematic areas.

In this approach, an MRI system acquires k-space data from a field of view and reconstructs an image series. The k-space data also is used to compute a confidence map depicting regions in the field of view affected by error sources. A parametric map is produced using the MRI image series but checked against the confidence map. Error-prone areas are avoided, removed or flagged so as not to contaminate the parametric map.
APPLICATIONS
  • Image reconstruction for MRI used to measure fat fraction or other phase base imaging
KEY BENEFITS
  • Improved parametric mapping
  • Overcomes systematic error and bias
Contact Information
For current licensing status, please contact Jeanine Burmania at jeanine@warf.org or 608-960-9846.
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