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Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

693
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
693

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相关实验视频

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切片间互补性增强了使用中央区域增强神经网络去除环形工件的功能.

Yikun Zhang1,2, Guannan Liu1,2, Zhanghao Chen1,2

  • 1Laboratory of Image Science and Technology, School of Computer Science and Engineering, Southeast University, Nanjing 210096, People's Republic of China.

Physics in medicine and biology
|September 30, 2025
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概括

由于复杂的探测器反应,光子计数探测器计算机断层扫描 (CT) 系统面临环形工件. 新的切片间互补性增强环物件去除 (ICE-RAR) 算法有效地减少这些物件,提高图像质量.

关键词:
中央地区加强神经网络计算机断层扫描 (CT) 是一种计算机断层扫描.深度学习是一种深度学习.切片之间的互补性.戒指工件 移除 删除 删除

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科学领域:

  • 医疗成像医学成像
  • 计算成像技术的成像
  • 用光子计数检测器进行检测

背景情况:

  • 在计算机断层扫描 (CT) 中,检测器反应不均会导致环形工件.
  • 对于光子计数探测器 (PCD),标准校准方法是不够的.
  • 基于PCD的CT系统中,有效的环形物移除 (RAR) 是非常重要的.

研究的目的:

  • 为基于PCD的CT开发一个高性能RAR算法.
  • 为了应对中部地区的挑战,移除文物.
  • 为了利用切片间的信息来增强文物消除.

主要方法:

  • 提出了切片间互补性增强的RAR (ICE-RAR) 算法.
  • 利用双分支神经网络进行全球和中央区域恢复.
  • 整合了切片间的互补性,以解决垂直探测器的不均性.

主要成果:

  • 在模拟和真实PCD CT数据集中,ICE-RAR有效地减少了环形工件.
  • 算法在重建的图像中保留了结构细节.
  • 在模拟数据上训练模型,将其概括为现实世界的PCD CT数据.

结论:

  • ICE-RAR证明了在基于PCD的CT系统中切实去除环形物件的巨大潜力.
  • 该方法在减少文物和保存图像细节方面都表现出有效性.
  • 该算法的从模拟到真实数据的概括能力突出显示了其实际适用性.