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相关概念视频

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

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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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Assessment of Diffusion and Perfusion01:17

Assessment of Diffusion and Perfusion

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Understanding and evaluating diffusion and perfusion is critical in assessing a patient's respiratory and circulatory health. These processes play key roles in maintaining the body's internal environment, ensuring that tissues receive adequate oxygen while waste products are efficiently removed.
The Role of Diffusion in Respiration
Diffusion is the process by which molecules move from an area of higher concentration to an area of lower concentration. In the respiratory system, this...
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相关实验视频

Updated: Jul 19, 2025

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

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降低扩散的MRI:分析的考虑和含义

Jose-Pedro Manzano-Patron1, Steen Moeller2, Jesper L R Andersson3

  • 1Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, UK.

bioRxiv : the preprint server for biology
|August 7, 2023
PubMed
概括
此摘要是机器生成的。

扩散核磁共振 (dMRI) 消噪方法可以提高信号质量,但可能导致空间分辨率损失. 对dMRI数据而言,复杂域的denoising比大小域的方法提供了更高的性能.

科学领域:

  • 医疗成像医学成像
  • 神经成像是一种神经成像.
关键词:
复杂的复杂的复杂.在 DTI 中,DTI 是指DTI.这就是MPPCA.马尔琴科-帕斯图尔是什么意思在NLM中,它是NLM.北欧国家 北欧国家噪音地板是一个噪音地板.不确定性 不确定性

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相关实验视频

Last Updated: Jul 19, 2025

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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

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  • 生物物理学的生物物理.

    • 背景情况:

    • 扩散MRI (dMRI) 数据中的噪声降低了测量准确度和精度.
    • 现有的dMRI否定方法的性能,特别是关于偏差和噪声底部效应,需要客观的表征.
    • 在客观评估各种dMRI拒绝技术的有效性方面仍然存在差距.

    结论:

    • 对于提高数据质量和实现超高分辨率成像等先进应用而言,dMRI denoising是至关重要的.
    • 对dMRI数据的复杂域处理对性能无效是有利的.
    • 需要进一步的研究来完善dMRI的除策略和黄金标准定义.