Palo Alto, California, November 19, 2007

Fovia Medical, Inc., a world leader in volume rendering technology, today announced that Gordon Harris, Ph.D., Director of the 3D Imaging Service and the Radiology Computer Aided Diagnostics Laboratory at the Massachusetts General Hospital, and an Associate Professor of Radiology at Harvard Medical School, has joined the company’s Medical Advisory Board.

Palo Alto, California, November 8, 2007

Fovia Medical, Inc., a world leader in volume rendering technology, today announced that Sandy Napel, Ph.D. and Geoffrey D. Rubin, M.D., Co-Directors of the Stanford Radiology 3D Medical Imaging Laboratory, have joined the company’s Medical Advisory Board.

Palo Alto, California, November 6, 2007

Fovia Medical, Inc., a world leader in volume rendering technology, today announced a research license agreement that will allow researchers in the 3D Laboratory at Massachusetts General Hospital (MGH) to integrate Fovia’s High Definition Volume Rendering® technology into their advanced imaging research.

Palo Alto, California, October 31, 2007

Fovia Medical, Inc., a world leader in volume rendering technology, and Drs. Sandy Napel, Ph.D., Professor of Radiology, and Geoffrey D. Rubin, M.D., Professor of Radiology, co-Directors of the Stanford University Department of Radiology’s 3D Laboratory, an internationally recognized academic leader in 3D imaging, today announced a research license agreement that will allow researchers in the 3D Laboratory at Stanford to integrate Fovia’s High Definition Volume Rendering® technology into their advanced imaging research.

Palo Alto, California, October 29, 2007

Fovia Medical, Inc., a leader in 3D graphics and volume visualization technology, today announced the release of its third generation High Definition Volume Rendering® software. Fovia’s thin-client engine allows users to take full advantage of multi-core processors and 64-bit architecture, resulting in a dramatic boost in system performance and allowing interactive HDVR™ rendering of the largest datasets generated by today’s medical imaging equipment.