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.
This blog post was originally published at Jon Peddie Research’s website. It is reprinted here with the permission of Jon Peddie Research. We need this technology now If any of you have attended any of my augmented reality lectures or read my book, you know I am an enthusiastic advocate of what I call consumer
What’s New: Intel Labs and the Perelman School of Medicine at the University of Pennsylvania (Penn Medicine) are co-developing technology to enable a federation of 29 international healthcare and research institutions led by Penn Medicine to train artificial intelligence (AI) models that identify brain tumors using a privacy-preserving technique called federated learning. Penn Medicine’s work
This market research report was originally published at Yole Développement’s website. It is reprinted here with the permission of Yole Développement. The smallest camera in the world for endoscopes is based on a fully wafer bonded technology, with CIS, packaging and optic on the same wafer. Reverse costing with: Analysis of the camera module structure,
This blog post was originally published at Intel’s website. It is reprinted here with the permission of Intel. Medical imaging data contains the power to save lives. Every tiny sliver of an image potentially holds the key to hugely important breakthroughs in treatment. And this year alone, hospitals produced over 50 petabytes of data, with
This blog post was originally published at Intel’s website. It is reprinted here with the permission of Intel. The COVID-19 coronavirus, since its initial outbreak in Wuhan, China, has quickly become a global pandemic, as declared by the World Health Organization (WHO). The number of confirmed cases has exceeded 577,531 globally as of March 27,
This article was originally published at MathWorks’ website. It is reprinted here with the permission of MathWorks. I’m pleased to publish another post from Barath Narayanan, University of Dayton Research Institute (UDRI), LinkedIn Profile. Co-author: Dr. Russell C. Hardie, University of Dayton (UD) Dr. Barath Narayanan graduated with MS and… Deep Learning for Medical Imaging:
Rudy Burger, Managing Partner, and Vini Jolly, Executive Director, both of Woodside Capital Partners, deliver the presentation “Vision Opportunities in Healthcare” at the Embedded Vision Alliance’s December 2019 Vision Industry and Technology Forum. Burger and Jolly outline trends and opportunities in computer vision for healthcare applications. “Vision Opportunities in Healthcare,” a Presentation from Woodside Capital
“Edge/Cloud Tradeoffs and Scaling a Consumer Computer Vision Product,” a Presentation from Cocoon Health
Pavan Kumar, Co-founder and CTO of Cocoon Health (formerly Cocoon Cam), delivers the presentation “Edge/Cloud Tradeoffs and Scaling a Consumer Computer Vision Product” at the Embedded Vision Alliance’s September 2019 Vision Industry and Technology Forum. Kumar explains how his company is evolving its use of edge and cloud vision computing in continuing to bring new
The Embedded Vision Summit was held on May 20-23, 2019 in Santa Clara, California, 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… May 2019 Embedded Vision Summit
This blog post was originally published at Intel's website. It is reprinted here with the permission of Intel. Intel has been an integral part of hospital technology for almost 50 years. From desktop computers to MRI scanners, diagnostic monitors, and even portable X-Ray machines, we have been at the forefront of healthcare transformation. So it