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.
Intel, EXOS Pilot 3D Athlete Tracking with Pro Football Hopefuls
What’s New: EXOS, a leader in the field of advancing human performance, is piloting Intel’s 3D Athlete Tracking (3DAT) technology in training aspiring professional athletes to reach their peak performance. As pro days loom, these athletes seek to take their game to the next level with 3DAT by leveraging artificial intelligence (AI) to gain actionable insights
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
Vini Jolly, Executive Director at Woodside Capital, presents the “Vision Opportunities in Healthcare” tutorial at the September 2020 Embedded Vision Summit. With advances in computer vision, AI/ML and data analytics, the pace of technological change continues to accelerate. Nowhere has the confluence of those technologies been more impactful than in Digital Health. Healthcare is an
“A Computer Vision-Based Personal Trainer That Runs On Your Phone,” a Presentation from Twenty BN
Roland Memisevic, CEO, Chief Scientist and Founder of Twenty BN, presents the “Computer Vision-Based Personal Trainer That Runs On Your Phone” tutorial at the September 2020 Embedded Vision Summit. In this presentation, Memisevic describes Twenty BN’s journey towards building an AI-powered personal trainer that runs on your phone. The trainer takes the form of an
“Multi-modal Re-identification: IOT + Computer Vision for Residential Community Tracking,” a Presentation from Seedland
Kit Thambiratnam, General Manager of the Seedland AI Center, presents the “Multi-modal Re-identification: IOT + Computer Vision for Residential Community Tracking” tutorial at the September 2020 Embedded Vision Summit. The recent COVID-19 outbreak necessitated monitoring in communities such as tracking of quarantined residents and tracking of close-contact interactions with sick individuals. High-density communities also have
Building and Deploying a Face Mask Detection Application Using NGC Collections
This technical article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. AI workflows are complex. Building an AI application is no trivial task, as it takes various stakeholders with domain expertise to develop and deploy the application at scale. Data scientists and developers need easy access to software
Intel’s 2021 Predictions for the Edge
Intel has been transforming computing at the edge for years – delivering customer value across a range of industries from health and life sciences to industrial to retail to telecommunications and beyond. The next few years promise to be exciting as analysts predict that by 2023, approximately 75% of data will be created outside the
What About Privacy?
This blog post was originally published at Ambarella’s website. It is reprinted here with the permission of Ambarella. In an age of universal surveillance, our sensing camera solutions offer a privacy-focused alternative. Security cameras are seemingly everywhere, all around us. They’ve become so ubiquitous that we barely even notice them anymore, monitoring and recording us
Implementing a Real-time, AI-Based, Face Mask Detector Application for COVID-19
This technical article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Businesses are constantly overhauling their existing infrastructure and processes to be more efficient, safe, and usable for employees, customers, and the community. With the ongoing pandemic, it’s even more important to have advanced analytics apps and services
“Enabling Embedded AI for Healthcare,” a Presentation from VeriSilicon
Shang-Hung Lin, Vice President of Machine Learning and Neural Processor Product Development at VeriSilicon, presents the “Enabling Embedded AI for Healthcare” tutorial at the September 2020 Embedded Vision Summit. Wearable electronics have started to become part of our daily lives, in the form of watches, wristbands, fitness trackers and the like. Advances in sensor design
