Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, 04103 Leipzig, Germany.
Magn Reson Med. 2010 Jul;64(1):15-22. doi: 10.1002/mrm.22488.
A good spatial resolution is essential for high precision segmentations of small structures in magnetic resonance images. However, any increase in the spatial resolution results in a decrease of the signal-to-noise ratio (SNR). In this article, this problem is addressed by a new image restoration technique that is used to partly compensate for the loss in SNR. Specifically, a two-stage hybrid image restoration procedure is proposed where the first stage is a Wiener wavelet filter for an initial denoising. The artifacts that will inevitably be produced by this step are subsequently reduced using a recent variant of anisotropic diffusion. The method is applied to magnetic resonance imaging data acquired on a 7-T magnetic resonance imaging scanner and compared with averaged multiple measurements of the same subject. It was found that the effect of image restoration procedure roughly corresponds to averaging across three repeated measurements.
良好的空间分辨率对于磁共振图像中小结构的高精度分割至关重要。然而，任何提高空间分辨率的方法都会导致信噪比（SNR）的降低。本文通过一种新的图像恢复技术来解决这个问题，该技术用于部分补偿 SNR 的损失。具体来说，提出了一种两阶段混合图像恢复过程，其中第一阶段是用于初始去噪的维纳小波滤波器。然后使用各向异性扩散的最新变体来减少这一步骤不可避免产生的伪影。该方法应用于在 7T 磁共振成像扫描仪上采集的磁共振成像数据，并与同一受试者的多次平均测量进行比较。结果发现，图像恢复过程的效果大致相当于对三次重复测量进行平均。
