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动态模式分解作为消除超高速功率多普勒图像噪声的框架
Baptiste Pialot1, Francesco Guidi2, Pauline Muleki-Seya3
1INSA-Lyon, Universite Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1294, F-69621, Lyon, France; Department of Information Engineering, University of Florence, 50139 Florence, Italy.
Computer methods and programs in biomedicine
|December 31, 2025
概括
一种新的动态模式分解 (DMD) 方法通过减少噪音显著提高了超快功率多普勒 (UPD) 超声波成像. 这提高了微血管可视化,以更好地诊断和监测疾病.
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
- 生物医学工程 生物医学工程
背景情况:
- 微血管成像对于诊断和监测病态至关重要.
- 超快速功率多普勒 (UPD) 超声波提供了便携性和高时间分辨率,但由于波浪传输不聚焦,其噪音水平较高.
研究的目的:
- 通过使用动态模式分解 (DMD) 来引入UPD成像的新型无色化方法.
- 为了提高UPD图像的信号噪声比 (SNR) 和对比噪声比 (CNR).
主要方法:
- 开发了一个新的框架,将DMD动态模式与超声波采集联系起来.
- 在UPD图像计算之前,从无噪声模式中删除了时间信号.
- 实现了基于能源的基于像素级的废弃模式的适应,用于局部噪声过.
主要成果:
- 基于DMD的消毒方法通过模拟,幻影研究和体内实验得到了验证.
- 与标准UPD图像相比,在体内SNR得到了高达26.0dB的改善,CNR得到了15.6dB的改善.
结论:
- 基于DMD的框架显著提高了UPD图像质量,以增强船舶可视化.
- 这种方法为血管超声波成像中高级动态分析提供了基础.
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