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.
October 2013 Embedded Vision Summit Technical Presentation: “Using FPGAs to Accelerate 3D Vision Processing: A System Developer’s View,” Ken Lee, VanGogh Imaging
Ken Lee, CEO of VanGogh Imaging, presents the "Using FPGAs to Accelerate 3D Vision Processing: A System Developer's View" tutorial within the "Implementing Vision Systems" technical session at the October 2013 Embedded Vision Summit East. Embedded vision system designers must consider many factors in choosing a processor. This is especially true for 3D vision systems,
October 2013 Embedded Vision Summit Technical Presentation: “Feature Detection: How It Works, When to Use It, and a Sample Implementation,” Marco Jacobs, videantis
Marco Jacobs, Technical Marketing Director at videantis, presents the "Feature Detection: How It Works, When to Use It, and a Sample Implementation" tutorial within the "Object and Feature Detection" technical session at the October 2013 Embedded Vision Summit East. Feature detection and tracking are key components of many computer vision applications. In this talk, Jacobs
Mario E. Munich, Vice President of Advanced Development at iRobot, presents the "Embedding Computer Vision in Everyday Life" keynote at the October 2013 Embedded Vision Summit East. Munich speaks about adapting highly complex computer vision technologies to cost-effective consumer robotics applications. Munich currently manages iRobot's research and advanced development efforts. He was formerly the CTO
Professor Masatoshi Ishikawa of Tokyo University delivers the keynote presentation, "High Speed Vision and Its Applications — Sensor Fusion, Dynamic Image Control, Vision Architecture, and Meta-Perception," at the July 2013 Embedded Vision Alliance Member Meeting. High speed vision processing and various applications based on it are expected to become increasingly common due to continued improvement
April 2013 Embedded Vision Summit Overview Presentation: “What Can You Do With Embedded Vision?,” Jeff Bier, Embedded Vision Alliance
Jeff Bier, founder of the Embedded Vision Alliance and co-founder and President of BDTI, presents the "What Can You Do With Embedded Vision?" overview presentation at the April 2013 Embedded Vision Summit. This presentation is intended for those new to embedded vision, and those seeking ideas for new embedded vision applications and technologies. Jeff Bier
Semiconductor and software advances are enabling medical devices to derive meaning from digital still and video images. By Brian Dipert Editor-in-Chief, Embedded Vision Alliance Senior Analyst, BDTI and Kamran Khan Technical Marketing Engineer, Xilinx This article was originally published in the May 2013 edition of MD+DI (Medical Device and Diagnostic Industry) Magazine. It is reprinted
By Jon Alexander, Technical Marketing Manager for ISM (Industrial, Scientific, Medical) Markets Xilinx Corporation Image enhancement functions – noise reduction, edge enhancement, dynamic range correction, digital zoom, scaling, etc – are key elements of many embedded vision designs, in improving the ability for downstream algorithms to automatically extract meaning from the image. Interface flexibility and
Embedded Vision Alliance Editor-in-Chief (and BDTI Senior Analyst) Brian Dipert and BDTI Senior Software Engineer Eric Gregori co-deliver an embedded vision application technology trends presentation at the December 2012 Embedded Vision Alliance Member Summit. Brian and Eric discuss embedded vision opportunities in mobile electronics devices. They quantify the market sizes and trends for smartphones and
September 2012 Embedded Vision Summit Presentation: “Introduction to Embedded Vision,” Jeff Bier, Embedded Vision Alliance
Jeff Bier, Founder of the Embedded Vision Alliance and co-founder and president of BDTI, presents the day-opening "Introduction to Embedded Vision" tutorial at the September 2012 Embedded Vision Summit. Topics discussed by Bier in his presentation include a technology overview, application examples, hardware, software and development tool trends, and an overview of the Embedded Vision
Gary Bradski presents the afternoon keynote at the September 2012 Embedded Vision Summit. Bradski is President and CEO of the OpenCV Foundation and Founder and Chief Technical Officer of Industrial Perception Inc. The "father of OpenCV" (the Open Source Computer Vision Library), Bradski has been the director of its development for more than 14 years,