PRODUCT CATALOG

San Luis Obispo, California – Vetel Diagnostics and the Vetel group of companies unveils its latest software update. Tibial Plateau Leveling Osteotomy (TPLO) automated measurements and reporting.

This is the latest tool available for Vetel’s Metron™ software platform. For over ten years Vetel has been a leader in developing these “superhuman” technologies for veterinary software.

TPLO measurements and reporting adds to Vetel’s growing list of existing automated measurements offered by Metron™ with Intellect Module. It joins the Norberg Hip Angle, Vertebral Heart Score, and multiple measurement utilities of the Equine Foot.

The new

San Luis Obispo, California – Vetel Diagnostics and the Vetel Group of companies continues to develop new diagnostic software for the technological advancement of veterinarians everywhere. Exclusively from Vetel comes the automatic measurement and reporting of the canine Norberg Hip Angle (NHA).

The NHA is the angle between the center of the head of the femur and the edge of the acetabulum measured in canine hip joints. The measurement of this angle provides a metric of the depth of the hip socket, and thus an indicator of risk for hip disease

San Luis Obispo, California – Vetel Diagnostics and the Vetel Group of companies are not afraid to break barriers and improve veterinary imaging technology. The most recent innovation is the release of Lumina III™ radiographic image processing technology.

Lumina III™ is the latest image processing technology used by Metron™, the image acquisition and PACS software for Vetel’s Enduro HD and Ruggedized Digital Radiography line. In previous versions, Lumina™ has always been the most modern image processing available on the market. Its progressive multiwavelet filtration technology generates a grain-less image that has

Artificial Intelligence (AI) can change the world of medicine. But how? And how will it affect the practice of veterinary medicine?

Deep learning is a type of AI in sophisticated software that utilizes neural networks, sometimes referred to as bioinformatics. When applied to diagnostic imaging, deep learning works by analyzing a bank of images to “learn” parts of the anatomy and judge what is considered “normal.” The more images the computer is given, the more precise its understanding becomes. Once the software learns what normal is, it can identify areas of