Camera Technology in Medical & Life Sciences: Top 5 Trends
There is hardly a technology that is not constantly developing, but there is a lot going on at Vision Technology, especially for Medical & Life Sciences. CCD sensors have largely been discontinued, but many manufacturers have already launched a new generation with the CMOS sensors. In addition, they are investing in the improvement of their CMOS sensors for example in order to optimize low-light image acquisition by means of backside illumination. The range of available interfaces is also expanding. New are MIPI CSI-2 for embedded vision applications and CXP-12 for particularly fast data transfer. In addition, Artificial Intelligence (AI) is also finding its way into Medical & Life Sciences. Image processing via AI enables completely new applications. As you can see, a lot is happening, learn more about the most exciting technology trends in our webinar.
Peter Behringer, Head of Product Management Medical at Basler, explains the most important trends in the field of camera technology for Medical & Life Sciences of today and tomorrow. Which technology is continuing to develop, which one has reached the end of its useful life and which one is currently conquering the stage?
In the webinar Peter will guide you through
- Image processing: Artificial Intelligence (AI)
- Sensors: bye bye, CCD
- Sensors: next gen image sensors
- Interfaces: expanding the range
- Cameras: improvements in low-light imaging
The webinar also features a question and answer session at the end.
Head of Product Management Medical
Peter Behringer is team leader in product management and responsible for Basler‘s product portfolio in the Medical & Life Sciences market. Prior to joining Basler, he completed his studies of medical engineering sciences at Universität zu Lübeck. During his studies he worked as a Research Trainee for prestigious institutions such as Charité Berlin and the Surgical Planning Laboratory of Harvard Medical School. Mr. Behringer published several academic papers with the focus on medical image processing.
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