Medical Applications for Embedded Vision
Embedded vision has the potential to become the primary treatment tool in hospitals and clinics
Embedded vision and video analysis have the potential to become the primary treatment tool in hospitals and clinics, and can increase the efficiency and accuracy of radiologists and clinicians. The high quality and definition of the output from scanners and x-ray machines makes them ideal for automatic analysis, be it for tumor and anomaly detection, or for monitoring changes over a period of time in dental offices or for cancer screening. Other applications include motion analysis systems, which are being used for gait analysis for injury rehabilitation and physical therapy.
Video analytics can also be used in hospitals to monitor the medical staff, ensuring that all rules and procedures are properly followed. For example, video analytics can ensure that doctors “scrub in” properly before surgery, and that patients are visited at the proper intervals.
What are the primary vision products used in medical systems?
Medical imaging devices including CT, MRI, mammography and X-ray machines, embedded with computer vision technology and connected to medical images taken earlier in a patient’s life, will provide doctors with very powerful tools to help detect rapidly advancing diseases in a fraction of the time currently required. Computer-aided detection or computer-aided diagnosis (CAD) software is currently also being used in early-stage deployments to assist doctors in the analysis of medical images by helping to highlight potential problem areas.

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September 2020 Embedded Vision Summit Slides
The Embedded Vision Summit was held online on September 15-25, 2020, as an educational forum for product creators interested in incorporating visual intelligence into electronic systems and software. The presentations delivered at the Summit are listed below. All of the slides from these presentations are included in PDF form. To… September 2020 Embedded Vision Summit

“Opportunities for Vision in Healthcare,” a Presentation from Woodside Capital
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“Enabling Embedded AI for Healthcare,” a Presentation from VeriSilicon
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