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Updated: Mar 15, 2026

Blood Flow Imaging with Ultrafast Doppler

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基于时间域噪声感知和DWT的激光多普勒血流信号的否定方法的研究

Quanxin Sun¹, Jie Duan¹, Hui Guo²

¹School of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun 130013, China.

Sensors (Basel, Switzerland)

|March 14, 2026

概括

这项研究介绍了激光多普勒流 (LDF) 信号的自适应性消噪算法,有效减少复合噪声并提高信号保真度. 这种新方法在具有挑战性的噪音条件下增强了血管血液动力学监测.

科学领域:

生物医学工程生物医学工程
信号处理信号处理
医疗成像医学成像

背景情况:

激光多普勒流 (LDF) 信号处理面临由复合噪声 (光斑,热,随机脉冲干扰) 和非静止性带来的挑战.
传统的值方法在LDF分析中难以平衡噪声抑制与信号保真.
精确的LDF信号处理对于有效的血管血液动力学监测至关重要.

研究的目的:

为LDF信号开发和验证一种适应性无声化算法,克服传统方法的局限性.
在存在复杂的噪声环境下提高LDF信号的保真度.
为准确的血管血动力学监测提供强大的解决方案.

主要方法:

提出了一个自适应性消噪算法,集成时间噪声感知和离散波波变换 (DWT).
建立了一个复合噪声模型,随后进行了五级DWT分解与局部能量检测.
采用SNR驱动的动态值策略,结合层间适应性分配和局部加权,随后改进了平滑.

主要成果:

模拟显示,从1dB输入SNR显著改善到15.45dB输出SNR,RMSE低 (0.05634),表现优于现有方法.
应用于血管幻影信号 (初始SNR -1.04 dB) 的结果是13.86 dB的输出SNR和0.00258 RMSE.
该算法与传统的波纹方法,局部方差和变化模式分解 (VMD) 相比,表现出更高的性能.

结论:

拟议的自适应消噪算法有效地抑制了LDF信号中的复合噪声和非静止性.
该方法实现了高保真度波形捕获,这对于精确的血管血动力学监测至关重要.
这种算法为LDF信号处理在复杂的噪音环境中提供了强大的和有效的解决方案.

关键词:

适应性去雾化适应性去雾化离散的波形变换.激光多普勒是一种激光.时间噪声感知时间噪声感知

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