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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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相关实验视频

Updated: Jul 4, 2025

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
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Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

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扫描特定的自主监督贝叶斯深度非线性反转用于低样本MRI重建.

Andrew P Leynes, Nikhil Deveshwar, Srikantan S Nagarajan

    IEEE transactions on medical imaging
    |February 9, 2024
    PubMed
    概括
    此摘要是机器生成的。

    本研究介绍了扫描特异自主监督贝叶斯深度非线性反转 (DNLINV),这是一种新的深度学习方法,用于更快的磁共振成像 (MRI) 重建,而不需要大型数据集或校准扫描.

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    High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
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    科学领域:

    • 医疗成像医学成像
    • 人工智能的人工智能
    • 计算科学 计算科学

    背景情况:

    • 由于数据采样限制,磁共振成像 (MRI) 采集受到缓慢的扫描时间的限制.
    • 监督深度学习 (DL) 加快了MRI,但需要广泛的全样本数据集.
    • 现有的无监督/自主监督DL方法仍然需要大型图像数据库.

    研究的目的:

    • 为加速MRI重建引入一种新的扫描特定深度学习方法.
    • 开发一种方法,消除了对大型数据集和校准扫描的需求.
    • 为了提高MRI重建在无校准并行成像和压缩传感中的性能.

    主要方法:

    • 开发了扫描特定的自我监督贝叶斯深度非线性反转 (DNLINV).
    • 使用深度图像先前类型的生成建模方法.
    • 在深度卷积神经网络规范化中采用近似贝叶斯推理.

    主要成果:

    • 在各种解剖学,对比度和采样模式中表现出改进的性能.
    • 超越现有的扫描特定的无校准并行成像和压缩传感方法.
    • 成功重建了MRI数据,仅使用来自单个扫描的部分样本数据.

    结论:

    • DNLINV提供了一种强大的,自我监督的,用于加速MRI重建的扫描特定方法.
    • 该方法克服了现有的监督和无监督DL技术的局限性.
    • DNLINV在MRI中推进了无校准并行成像和压缩传感.