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相关概念视频

Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

91
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
91
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

83
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
83

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相关实验视频

Updated: Jul 5, 2025

Measurement of X-ray Beam Coherence along Multiple Directions Using 2-D Checkerboard Phase Grating
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提高多角度平面波形图像质量,使用最小方差束成形与自适应信号一致性.

Che-Chou Shen1, Chun-Lin Huang1

  • 1Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 106335, Taiwan.

Sensors (Basel, Switzerland)
|January 11, 2024
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概括
此摘要是机器生成的。

适应式延迟乘和和 (ADMAS) 方法通过局部调整信号连贯性来提高超声图像质量. 这种新技术提高了分辨率和对比度,而不牺牲背景斑点质量,优于传统方法.

关键词:
适应式延迟乘法和总和.延迟-乘法-和-和的结果.最小的差异是最小的差异.平面波形象成像 波形象成像信号的一致性信号的一致性

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相关实验视频

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科学领域:

  • 医疗成像医学成像
  • 超声波技术 超声波技术 超声波技术
  • 信号处理 信号处理

背景情况:

  • 超声成像中的常规连贯平面波组合 (CPWC) 由于标准的延迟和总和束成形,提供了有限的质量.
  • 延迟乘和和 (DMAS) 通过结合信号连贯性来提高图像质量,但通常会降低背景斑点.
  • 现有的DMAS方法采用全球一致性值,影响整体图像质量和对比度与噪声比率 (CNR).

研究的目的:

  • 为超声波多角度平面波成像引入一个自适应的DMAS (ADMAS) 算法.
  • 通过调整信号连贯性以适应局部图像特征来保持背景斑点质量和CNR.
  • 将ADMAS与最小方差 (MV) 束形进行组合,以提高图像分辨率.

主要方法:

  • 开发了自适应的DMAS (ADMAS) 算法,使信号连贯性取决于局部图像区域.
  • 集成的ADMAS具有最小方差 (MV) 束形,优化沿平面波传输角度 (Tx) 优化MV估计.
  • 评估了TxMV-ADMAS光束成形方法,使用PICMUS数据集进行多角度平面波成像.

主要成果:

  • 与CPWC相比,TxMV-ADMAS显著提高了图像质量.
  • 虽然传统的DMAS提高了分辨率 (0.57mm到0.24mm) 和对比度 (27.0dB到38.0dB),但它降低了CNR (12.8到11.3).
  • 拟议的ADMAS算法恢复了CPWC水平的CNR,同时保持了增强的分辨率和对比度.

结论:

  • 拟议的TxMV-ADMAS光束成形方法有效地提高了超声波图像的分辨率和对比度.
  • 亚德马斯保留了背景斑质量和CNR,克服了传统全球一致性方法的局限性.
  • 这种适应性方法为多角度平面波超声波成像提供了卓越的图像质量.