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使用时间卷积网络对MRI梯度系统进行建模:通过预测读出梯度错误来改进重建

Jonathan B Martin1, Hannah E Alderson1,2, John C Gore1,2,3

  • 1Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA.

Magnetic resonance in medicine
|August 19, 2025
PubMed
概括

这项研究引入了一种新的卷积神经网络模型,以准确预测MRI中的非线性梯度扭曲. 这种先进的方法提高了图像质量和扩散参数映射,优于传统技术.

关键词:
深度学习是一种深度学习.扩散磁力共振成像 (MRI) 扩散梯度纠正正正梯度的纠正图像重建 图像重建机器学习是机器学习.非卡特西斯轨迹的轨迹时间卷积网络时间序列预测时间序列预测

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