Full-stack Intelligent Medical Ultrasound
ID:32 View Protection:ATTENDEE Updated Time:2021-11-02 20:03:37 Hits:1725 Invited speech

Start Time:2021-11-14 13:30(Asia/Shanghai)

Duration:25min

Session:PS1 Plenary Session 1 » NM2Workshop on NM Session 2

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Abstract
Large user differences and low standardization are the main challenges faced by medical ultrasound diagnosis. Shenzhen University's MUSIC (Medical UltraSound Image Computing, www.music-bme.net) laboratory has long been committed to the standardization, quantification and intelligent research of ultrasound diagnosis by making use of image analysis, artificial intelligence and robotics technologies. This talk will introduce in detail the research and thinking of the MUSIC laboratory in full-stack intelligent medical ultrasound, including the detection of standard planes, the measurement of biological parameters, and computer-aided diagnosis. It will reveal the use of cutting-edge artificial intelligence methods to solve ultrasound diagnosis faced challenges.
 
Keywords
Speaker
Dong Ni
Professor Shenzhen University

Professor, Shenzhen University
*Associate Dean, School of Biomedical Engineering, Shenzhen University
*Director of the Laboratory for Medical UltraSound Image Computing (MUSIC), Shenzhen University
*MICCAI Board Member

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Important Date
  • Conference Date

    Nov 13

    2021

    to

    Nov 14

    2021

  • Sep 30 2021

    Contribution Submission Deadline

  • Nov 14 2021

    Registration deadline

Sponsored By
Medical Physics Branch of Chinese Society of Biomedical Engineering
IEEE Beijing Section
Life Electronics Society of Chinese Institute of Electronics
Organized By
Anhui Biomedical Engineering Society.
University of Science and Technology of China
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