Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Imaging Studies II: Ultrasonography01:24

Imaging Studies II: Ultrasonography

348
IntroductionUltrasonography, or renal ultrasound, is a noninvasive medical imaging technique that uses high-frequency sound waves to visualize the kidneys, ureters, bladder, and surrounding tissues.Indications for Urinary System UltrasonographyUrinary system ultrasonography is indicated in various clinical scenarios, such as:Kidney Stones (Urolithiasis): To detect and monitor the size and presence of kidney or urinary tract stones.Hydronephrosis: To assess the dilation of the renal pelvis and...
348
Ultrasonography01:17

Ultrasonography

7.3K
Ultrasonography is an imaging technique that uses high-frequency sound waves to visualize the body's internal structures. It is a non-invasive and safe procedure that does not involve the use of ionizing radiation, making it widely used in various medical fields. Ultrasonography is used to study heart function, blood flow in the neck or extremities, certain conditions such as gallbladder disease, and fetal growth and development.
During an ultrasonography procedure, a handheld device called...
7.3K
Deconvolution01:20

Deconvolution

541
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
541
Ultrasound II: Endoscopic Ultrasound and FibroScan01:25

Ultrasound II: Endoscopic Ultrasound and FibroScan

541
Endoscopic Ultrasound (EUS) and FibroScan are valuable diagnostic tools in gastroenterology and hepatology, each with specific applications and techniques.
Endoscopic Ultrasound (EUS):
541

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Resonant Eddy Current Sensor Design for Corrosion Detection of Reinforcing Steel.

Sensors (Basel, Switzerland)·2024
Same author

Small Ultrasound-Based Corrosion Sensor for Intraday Corrosion Rate Estimation.

Sensors (Basel, Switzerland)·2022
查看所有相关文章

相关实验视频

Updated: Jan 15, 2026

Formulation and Acoustic Modulation of Optically Vaporized Perfluorocarbon Nanodroplets
07:44

Formulation and Acoustic Modulation of Optically Vaporized Perfluorocarbon Nanodroplets

Published on: July 16, 2021

2.5K

涂层厚度估计使用CNN增强超声波和基于回声的解卷.

Marina Perez-Diego1,2, Upeksha Chathurani Thibbotuwa1, Ainhoa Cortés1,2

  • 1CEIT-Basque Research and Technology Alliance (BRTA), Manuel Lardizabal 15, 20018 Donostia-San Sebastián, Spain.

Sensors (Basel, Switzerland)
|October 16, 2025
PubMed
概括

这项研究引入了一种新的超声波方法,可以准确测量涂层厚度,即使有重叠的回声. 该技术使用信号分析和1D卷积神经网络在离岸应用中进行可靠的非破坏性测试.

关键词:
在美国,CNN是CNN.估计涂层厚度的估计.解卷模拟的解卷模型超声波脉冲回声 超声波脉冲回声

更多相关视频

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

2.3K
3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography
07:01

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography

Published on: October 24, 2019

10.2K

相关实验视频

Last Updated: Jan 15, 2026

Formulation and Acoustic Modulation of Optically Vaporized Perfluorocarbon Nanodroplets
07:44

Formulation and Acoustic Modulation of Optically Vaporized Perfluorocarbon Nanodroplets

Published on: July 16, 2021

2.5K
A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

2.3K
3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography
07:01

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography

Published on: October 24, 2019

10.2K

科学领域:

  • 材料科学 材料科学 材料科学
  • 声学 声学 在声学方面
  • 非破坏性测试 不破坏性测试

背景情况:

  • 涂层退化监测对于海上结构完整性和防腐蚀至关重要.
  • 准确的涂层厚度估计对于评估保护层性能至关重要.
  • 传统的超声波脉冲回声方法在与距离较近的接口的重叠回声作斗争,这阻碍了精确的厚度测量.

研究的目的:

  • 开发一种基于超声波的先进方法来准确估计涂层厚度.
  • 克服传统方法在解决紧密间隔的声学接口方面的局限性.
  • 在苛刻的环境中,使涂层完整性的可靠非破坏性监测成为可能.

主要方法:

  • 开发了一种新的解卷模型,使用两个连续的后墙回声来隔离传播路径信息.
  • 一个1D卷积神经网络 (1D-CNN) 用于在反射性函数内增强检测涂层厚度.
  • 合成信号是使用有限差异时间域 (FDTD) 模拟 (k-Wave MATLAB工具箱) 来生成的,用于训练1D-CNN模型.

主要成果:

  • 该方法在各种条件下成功估计了钢基板的前侧涂层厚度 (60μm740μm).
  • 对于一个8 MHz的超声波传感器,最小可检测厚度大约为λ/5.
  • 在合成数据上,1D-CNN模型实现了大约8μm的精度.

结论:

  • 提出的基于超声波回声的方法为涂层厚度估计提供了强大的解决方案.
  • 该方法显示了在现实应用中可靠监测涂层厚度变化的巨大潜力.
  • 这种技术增强了离岸行业及其他领域的非破坏性测试能力.