About GOPView iRVUltra
With the GOPView iRVUltra, ContextVision is once again innovating the diagnostic imaging space by integrating a new real-time image enhancement filter. The company's proprietary and complex algorithm is now able to accurately define the movements between the images, frame by frame, pixel by pixel, to quickly find structures and orientation for interventional procedures in real time and without time gaps. The result: enhanced low-dose images that offer superior clarity and higher contrast, regardless of the detector solution used.
"Interventional radiologists always look to strike an ideal balance between the required image quality and the radiation dose for any given procedure," said Anita Tollstadius, CEO of ContextVision. "As a result, they rely heavily on the newest advancements in image quality enhancement and dose reduction technologies. Generally, it takes an increased dose to enhance the image quality. With the GOPView iRVUltra, radiologists no longer have to compromise, as superior image quality can be achieved despite low dose images."
Both the MAMMO PLUSViewCAD and the GOPView iRVUltra will be showcased at ContextVision's booth in hall Expo E, booth 517 at the European Congress of Radiology (ECR), March 3-7, 2011 in Vienna, Austria.
About ContextVision
ContextVision is the leading independent developer in medical imaging enhancement, analysis and processing technologies, serving leading OEMs and distributors for 27 years. ContextVision's embedded imaging software is relied upon daily by thousands of users around the globe. ContextVision's patented GOP algorithm allows unprecedented image quality to be achieved by simultaneously enhancing fine structure while reducing noise and speckle across MRI, X-Ray, Ultrasound, CT, and IR.
[1] http://www.cancer.gov/cancertopics/factsheet/cancer-advances-in-focus/breast
[2] http://www.medscape.com/viewarticle/412216
[3] http://www.radiologyinfo.org/en/info.cfm?pg=mammo
[4] Improvement in Sensitivity of Screening Mammography with Computer-Aided Detection: A Multiinstitutional Trial; Rachel F. Brem1, Janet Baum2, Mary Lechner3, Stuart Kaplan4, Stuart Souders5, L. Gill Naul6 and Jeff Hoffmeister7; American Journal of Roentgenology, 2003.
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