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相关概念视频

Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

449
Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
449

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PPEA:基于多任务共享姿势估计变压器的个性化定位和曝光助手.

Jie Zhao1,2, Jianqiang Liu2, Chunfeng Yang1

  • 1Laboratory of Image Science and Technology, School of Computer Science and Engineering, Southeast University, Nanjing, China.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
|August 13, 2025
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概括
此摘要是机器生成的。

这项研究介绍了一种人工智能助理,用于手和脚的数字放射 (DR). 它自动识别患者的位置,并推最佳的曝光参数,以提高图像质量和减少重拍.

关键词:
数字辐射学数字辐射学自动曝光控制自动曝光控制脚姿势估计 脚姿势估计手的姿势估计手的姿势估计.患者的位置定位.变压器变压器变压器变压器

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科学领域:

  • 医疗成像医学成像
  • 人工智能的人工智能
  • 放射学 放射学 放射学 放射学

背景情况:

  • 准确的患者定位和曝光设置对于手脚数字放射 (DR) 诊断质量至关重要.
  • 患者解剖学和定位要求的变化需要个性化的方法来优化成像协议.
  • 尽量减少图像重拍对于效率和减少患者辐射暴露至关重要.

研究的目的:

  • 开发和评估一个个性化的定位和曝光助手手和脚DR.
  • 为了实现手和脚位置的自动识别,并推量身定制的暴露参数.
  • 提高诊断准确度,减少临床放射学设置中的错误.

主要方法:

  • 开发了一个由三个模块组成的助手:用于姿势估计的渐进式代手脚追踪器 (PIHFT),用于强大的手脚姿势识别的多任务共享姿势估计变压器 (MTSPET),以及用于参数推的领域专业知识嵌入式定位和曝光助手 (DEPEA).
  • 在两个新收集的数据集上进行MTSPET培训,证明了与MediaPipe等现有方法相比的卓越性能,用于手姿势估计和成功将学习转移到脚姿势估计.
  • 在DEPEA中将关键点坐标与临床要求集成,以推断数字自动暴露控制 (DAEC) 的暴露区域和感兴趣区域 (ROI).

主要成果:

  • 与MediaPipe相比,MTSPET实现了优越的手姿势估计,并有效地将其应用于足姿势估计.
  • DEPEA模块成功地将姿势数据与临床专业知识相结合,以确定定位和暴露参数.
  • 一项初步的临床试验表明,助理的输出与手册注释之间有很强的一致性,验证了其临床实用性.

结论:

  • 建议的个性化定位和曝光助手有效地自动识别DR中的手和脚位置.
  • 该系统为曝光参数提供准确的建议,有助于提高图像质量和减少重拍.
  • 这种由人工智能驱动的方法为医疗放射学中个性化,针对患者的成像策略奠定了基础,提高了诊断结果.