Full-stack Intelligent Medical Ultrasound
编号:32 访问权限:仅限参会人 更新:2021-11-02 20:03:37 浏览:599次 特邀报告

报告开始:2021年11月14日 13:30(Asia/Shanghai)

报告时间:25min

所在会场:[PS1] Plenary Session 1 [NM2] Workshop on NM Session 2

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摘要
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.
 
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报告人
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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重要日期
  • 会议日期

    11月13日

    2021

    11月14日

    2021

  • 09月30日 2021

    报告提交截止日期

  • 11月14日 2021

    注册截止日期

主办单位
IEEE北京分会
中国生物医学工程学会医学物理分会
中国电子学会生命电子学分会
承办单位
中国科学技术大学
安徽省生物医学工程学会
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