GOPiCE real-time volumetric imaging incorporated in Medison's ultrasound units

“The real-time volumetric imaging of GOPiCE will be available across the globe thanks to Medison, an ultrasound market leader”

GOPiCE US provides clinicians unprecedented image enhancement capabilities

ContextVision (OSE:COV), the software imaging partner for the most recognized medical imaging manufacturers worldwide, today announced that Medison, a world-class manufacturer of advanced ultrasound technology, will incorporate ContextVision's volumetric image enhancement tool, GOPiCE® US, into its ultrasound units during the second half of 2010. GOPiCE, the first real-time volumetric filtering software for ultrasound, offers clinicians the ability to see areas never seen before, including anatomies comprised of deep tissue and behind bone.

GOPiCE filters three-dimensional ultrasound volumes, removing speckle and other artifacts, while simultaneously extending the clinician's vision to planes previously hidden, such as the regions of the fetal brain previously hidden by speckle and noise in two-dimensional and three-dimensional ultrasound images.

"The real-time volumetric imaging of GOPiCE will be available across the globe thanks to Medison, an ultrasound market leader," said Anita Tollstadius, CEO of ContextVision. "Based on initial reaction to GOPiCE's capabilities, ContextVision plans to adapt the technology to extend its use across other modalities."

In 2009, Thomas Jefferson University conducted a clinical evaluation with GOPiCE. The study, presented at AIUM in March, concludes that GOPiCE US offers significantly better image quality compared to competing image enhancement technologies. Dr. Flemming Forsberg, Department of Radiology, led the study, which compared unprocessed volumes, volumes processed with two-dimensional processing software, and those processed with GOPiCE's three-dimensional real-time technologies.

Like all ContextVision products, GOPiCE US relies on an adaptive algorithm, GOP®, which mimics the human eye's method of finding information and analyzing structures. This enables the software to distinguish between true and false information (e.g. noise, artifacts) and accurately identify true structures.