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.

“A Highly Data-Efficient Deep Learning Approach,” a Presentation from Samsung

Patrick Bangert, Vice President of AI at Samsung, presents the “Highly Data-Efficient Deep Learning Approach” tutorial at the May 2021 Embedded Vision Summit. Many applications, such as medical imaging, lack the large amounts of data required for training popular CNNs to achieve sufficient accuracy. Often, these same applications suffer from an imbalanced class distribution problem

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“Improving Nursing Care with Privacy-Sensitive Edge Computer Vision,” a Presentation from Kepler Vision Technologies

Harro Stokman, Chief Executive Officer and Founder of Kepler Vision Technologies, presents the “Improving Nursing Care with Privacy-Sensitive Edge Computer Vision” tutorial at the May 2021 Embedded Vision Summit. Around the world, there is a serious and growing shortage of nurses. Nursing care at night is a particular challenge because night shifts are less attractive

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Case Study: Genetic Screening Using CNNs in PerceptiLabs

This blog post was originally published at PerceptiLabs’ website. It is reprinted here with the permission of PerceptiLabs. One group of scientists leveraging ML is the Buchser lab at Washington University in Saint Louis School of Medicine in the Department of Genetics. There, Dr. Buchser and his team are working in functional genomics, High-Throughput Screening,

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Building Real-time Dermatology Classification with NVIDIA Clara AGX

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. The most commonly diagnosed cancer in the US today is skin cancer. There are three main variants: melanoma, basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). Though melanoma only accounts for roughly 1% of all skin

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Intel-Powered AI Solution Helps Reduce Diabetic Vision Loss

What’s New: Sankara Eye Foundation and Singapore-based Leben Care are deploying a comprehensive retina risk assessment software-as-a-service platform in India. Netra.AI, the cloud-based artificial intelligence (AI) solution, is powered by Intel® technology and uses deep learning to identify retinal conditions in a short span of time with the accuracy level of human doctors. Netra.AI can accurately identify diabetic retinopathy

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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

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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

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“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

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“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

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Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.



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