Technology Listings

Automated Kidney Identification for Magnetic Resonance Images


A software tool that can automatically identify kidney tissue in serial magnetic resonance (MR) images.

Key Benefits
  • Can replace time consuming and challenging manual identification of the kidney.
  • Able to discern the border of the kidney in serial MR images even in areas of low contrast.
Market Summary

Reliable evaluation of the size of the kidney is important tool in the evaluation of kidney function. This measurement becomes increasingly important in the case of serial MRI as it allows for a non-invasive monitoring and assessment of the kidneys. Serial MRI of the kidney is most often used to monitor patients with polycystic kidney disease. This disease results in the development of fluid-filled cysts in the kidney and its progression is best tracked through serial kidney MRI. Approximately 314,000 people in the US have Polycystic kidney disease. Additionally, 26 million American adults have chronic kidney disease, which may require kidney imaging by MRI as part of both their diagnosis and long-term care.

Technical Summary

Emory researchers have developed a new software tool that is able to identify kidney tissue in serial MRI automatically. The method involved allows the software to learn and take into account both kidney shape and textural features. The software can then accurately identify the weakly contrasted boundaries of the kidney near the liver, spleen, and pancreas. Because implementation of this software results in fast and accurate kidney segmentation, it can replace the need for time-consuming and challenging manual kidney identification.

Developmental Stage

Method has been evaluated and validated with 7 MRI data sets from mice.

Patent Information
Tech ID: 11231
Published: 12/4/2013

Rajsekhar Guddneppanavar
Licensing Associate
Emory University

Baowei Fei
Hamed Akbari