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用于实时磁共振成像的图像去噪

Image denoising for real-time MRI.

作者信息

Klosowski Jakob, Frahm Jens

机构信息

Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für biophysikalische Chemie, Göttingen, Germany.

出版信息

Magn Reson Med. 2017 Mar;77(3):1340-1352. doi: 10.1002/mrm.26205. Epub 2016 Apr 15.

Abstract

PURPOSE

To develop an image noise filter suitable for MRI in real time (acquisition and display), which preserves small isolated details and efficiently removes background noise without introducing blur, smearing, or patch artifacts.

THEORY AND METHODS

The proposed method extends the nonlocal means algorithm to adapt the influence of the original pixel value according to a simple measure for patch regularity. Detail preservation is improved by a compactly supported weighting kernel that closely approximates the commonly used exponential weight, while an oracle step ensures efficient background noise removal. Denoising experiments were conducted on real-time images of healthy subjects reconstructed by regularized nonlinear inversion from radial acquisitions with pronounced undersampling.

RESULTS

The filter leads to a signal-to-noise ratio (SNR) improvement of at least 60% without noticeable artifacts or loss of detail. The method visually compares to more complex state-of-the-art filters as the block-matching three-dimensional filter and in certain cases better matches the underlying noise model. Acceleration of the computation to more than 100 complex frames per second using graphics processing units is straightforward.

CONCLUSION

The sensitivity of nonlocal means to small details can be significantly increased by the simple strategies presented here, which allows partial restoration of SNR in iteratively reconstructed images without introducing a noticeable time delay or image artifacts. Magn Reson Med 77:1340-1352, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

摘要

目的

开发一种适用于磁共振成像实时(采集和显示)的图像噪声滤波器,该滤波器能保留微小孤立细节,并有效去除背景噪声,且不会引入模糊、拖影或块状伪影。

理论与方法

所提出的方法扩展了非局部均值算法,根据一种简单的块正则性度量来调整原始像素值的影响。通过紧密逼近常用指数权重的紧支加权核来改善细节保留,同时一个神谕步骤确保有效去除背景噪声。对通过正则化非线性反演从具有明显欠采样的径向采集中重建的健康受试者实时图像进行去噪实验。

结果

该滤波器使信噪比(SNR)提高至少60%,且无明显伪影或细节损失。在视觉上,该方法与更复杂的先进滤波器(如块匹配三维滤波器)相当,并且在某些情况下能更好地匹配潜在噪声模型。使用图形处理单元将计算速度提高到每秒100多个复数帧很容易实现。

结论

通过本文提出的简单策略可显著提高非局部均值对小细节的敏感性,这使得在迭代重建图像中能部分恢复信噪比,而不会引入明显的时间延迟或图像伪影。《磁共振医学》77:1340 - 1352, 2017。© 2016国际磁共振医学学会。

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