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相关概念视频

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

5.2K
Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
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Deconvolution01:20

Deconvolution

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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...
163
¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

1.0K
Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are...
1.0K
¹³C NMR: ¹H–¹³C Decoupling01:04

¹³C NMR: ¹H–¹³C Decoupling

1.1K
The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...
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Imaging Studies for Cardiovascular System IV: CMRI01:21

Imaging Studies for Cardiovascular System IV: CMRI

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Cardiovascular magnetic resonance imaging, or CMRI, is a non-invasive diagnostic test that employs a magnetic field and radiofrequency waves to create precise images of the heart and arteries. It provides comprehensive information about cardiac anatomy, function, perfusion, and tissue characterization without ionizing radiation.IndicationsCMRI diagnoses various heart conditions, including tissue damage from heart attacks, ischemic heart disease, myocarditis, aortic issues (tears, aneurysms,...
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相关实验视频

Updated: Jul 11, 2025

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

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将变化模式分解与正规化技术相结合,以消除MRI数据的噪音.

Krzysztof Brzostowski1, Rafał Obuchowicz2

  • 1Department of Computer Science and Systems Engineering, Faculty of Information and Communication Technology, Wrocław University of Science and Technology, Wrocław 50-370, Poland.

Magnetic resonance imaging
|November 16, 2023
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种使用变化模式分解和规范化的新方法,有效地从MRI数据中去除噪声,改善图像质量,特别是在具有挑战性的条件下.

关键词:
生物医学成像学 生物医学成像学图像过器可以过图像磁共振成像技术 磁共振成像技术噪声 噪声 噪声

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Last Updated: Jul 11, 2025

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
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Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
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科学领域:

  • 医疗成像医学成像
  • 信号处理 信号处理
  • 计算科学 计算科学

背景情况:

  • 磁力共振成像数据经常受到噪音的影响,这可能会降低图像质量和诊断准确度.
  • 传统的无声化方法可能会与复杂的噪声模式作斗争,特别是MRI固有的Rician噪声.
  • 规范化技术对于解决像图像消噪等不良问题至关重要.

研究的目的:

  • 提出一种新且有效的方法来消除磁共振成像 (MRI) 数据.
  • 通过抑制Rician噪声来提高MRI图像的质量.
  • 对现有最先进的技术进行对比,评估拟议的脱雾方法的性能.

主要方法:

  • 拟议的方法结合了调节技术和变化模式分解 (VMD).
  • 使用2D VMD算法将MRI成像数据分解为内在模式.
  • 合拉索信号近似器应用于噪声抑制的分解模式.

主要成果:

  • 与参考方法相比,该新方法在消除MRI数据方面表现优越.
  • 包括PSNR,SSIM,HEN,QILV和度指数在内的定量指标证实了它的有效性.
  • 该算法在严重噪声条件下表现出特别高的消噪性能,在模拟和真实MRI图像上得到验证.

结论:

  • 拟议的规范化和基于VMD的方法为MRI无声化提供了一个强大的解决方案.
  • 这种方法显著提高了MRI图像的信号噪声比和结构完整性.
  • 研究结果表明,这种技术对于增强医学图像分析和解释非常有价值.