四位数与线性模型对比,以估计平均散射间距作为活体组织外温度的函数
Guillermo Cortela1, Wagner C A Pereira2, Carlos Negreira1
1Laboratorio de Acustica Ultrasonora, Instituto de Física-Facultad de Ciencias, Montevideo 11400, Uruguay.
Ultrasonics
|June 26, 2023
概括
这项研究通过分离热膨胀和速度变化来改善超声波温度估计. 与线性模型相比,二次模型显著减少了与超声波治疗期间准确监测温度的线性模型相比的错误.
科学领域:
- 生物医学工程 生物医学工程
- 声学 声学 在声学方面
- 医疗成像医学成像
背景情况:
- 诊断超声波可以估计超声波治疗期间的温度.
- 目前的方法依赖于热膨胀和速度变化的结合,假设直线温度依赖.
- 解脱这些因素对于提高准确性至关重要.
研究的目的:
- 为了区分热膨胀和速度变化对散射器间距的影响.
- 使用超声波开发一个更准确的温度估计模型.
- 为了验证拟议的模型在ex vivo肌肉组织中的有效性.
主要方法:
- 利用一种新的实验设置,通过透过传输测量绝对超声速.
- 估计的平均散射器间距使用脉冲回声反散信号的光谱分析.
- 提出并比较了热膨胀系数适配的线性和二次模型.
主要成果:
- 成功解的速度变化和热膨胀对散射器间距进化的贡献.
- 二级模型实现了温度估计的4.8%的平均平方误差.
- 线性模型在29.5-47°C范围内产生了11%的平均平方误差.
结论:
- 热膨胀的二次模型在基于超声波的温度估计中提供了更高的准确性.
- 分离物理参数可以提高治疗性超声波期间的非侵入性温度计的可靠性.
- 这种方法有望提高超声波治疗的安全性和有效性.
更多相关视频
06:42Plasmonic Photothermal Cancer Therapy: Nanoparticle-embedded Tumor-tissue-mimicking Phantoms for Visualizing Photothermal Temperature Distribution
Published on: May 9, 2025
541
11:57Measuring Spatially- and Directionally-varying Light Scattering from Biological Material
Published on: May 20, 2013
13.6K
相关概念视频
Calculating and Interpreting the Linear Correlation Coefficient
6.0K
The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable, x, and the dependent variable, y. Hence, it is also known as the Pearson product-moment correlation coefficient. It can be calculated using the following equation:
6.0K
Calibration Curves: Linear Least Squares
1.4K
A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
For data that follow a straight line, the standard method for fitting is the linear...
1.4K
