PET Centre, Institute of Radiopharmacy, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany.
EJNMMI Res. 2011 Oct 5;1(1):23. doi: 10.1186/2191-219X-1-23.
To achieve an acceptable signal-to-noise ratio (SNR) in PET images, smoothing filters (SF) are usually employed during or after image reconstruction preventing utilisation of the full intrinsic resolution of the respective scanner. Quite generally Gaussian-shaped moving average filters (MAF) are used for this purpose. A potential alternative to MAF is the group of so-called bilateral filters (BF) which provide a combination of noise reduction and edge preservation thus minimising resolution deterioration of the images. We have investigated the performance of this filter type with respect to improvement of SNR, influence on spatial resolution and for derivation of SUVmax values in target structures of varying size.
Data of ten patients with head and neck cancer were evaluated. The patients had been investigated by routine whole body scans (ECAT EXACT HR+, Siemens, Erlangen). Tomographic images were reconstructed (OSEM 6i/16s) using a Gaussian filter (full width half maximum (FWHM): Γ0 = 4 mm). Image data were then post-processed with a Gaussian MAF (FWHM: ΓM = 7 mm) and a Gaussian BF (spatial domain: ΓS = 9 mm, intensity domain: ΓI = 2.5 SUV), respectively. Images were assessed regarding SNR as well as spatial resolution. Thirty-four lesions (volumes of about 1-100 mL) were analysed with respect to their SUVmax values in the original as well as in the MAF and BF filtered images.
With the chosen filter parameters both filters improved SNR approximately by a factor of two in comparison to the original data. Spatial resolution was significantly better in the BF-filtered images in comparison to MAF (MAF: 9.5 mm, BF: 6.8 mm). In MAF-filtered data, the SUVmax was lower by 24.1 ± 9.9% compared to the original data and showed a strong size dependency. In the BF-filtered data, the SUVmax was lower by 4.6 ± 3.7% and no size effects were observed.
Bilateral filtering allows to increase the SNR of PET image data while preserving spatial resolution and preventing smoothing-induced underestimation of SUVmax values in small lesions. Bilateral filtering seems a promising and superior alternative to standard smoothing filters.
为了在 PET 图像中获得可接受的信噪比 (SNR),通常在图像重建期间或之后使用平滑滤波器 (SF),从而阻止利用各自扫描仪的固有分辨率。为此,通常使用高斯形状的移动平均滤波器 (MAF)。MAF 的一种潜在替代方法是所谓的双边滤波器 (BF) 组,它提供了降噪和边缘保留的组合,从而最小化图像分辨率的恶化。我们研究了这种滤波器类型在提高 SNR、对空间分辨率的影响以及推导不同大小目标结构的 SUVmax 值方面的性能。
评估了十位头颈部癌症患者的数据。这些患者接受了常规全身扫描 (ECAT EXACT HR+,西门子,埃尔兰根)。使用高斯滤波器 (半峰全宽 (FWHM):Γ0 = 4 mm) 对断层图像进行重建 (OSEM 6i/16s)。然后,使用高斯 MAF (FWHM:ΓM = 7 mm) 和高斯 BF (空间域:ΓS = 9 mm,强度域:ΓI = 2.5 SUV) 对图像数据进行后处理。对 SNR 和空间分辨率进行了评估。对 34 个病变 (体积约为 1-100 毫升) 进行了分析,以获得原始图像以及 MAF 和 BF 滤波图像中 SUVmax 的值。
选择的滤波器参数使两种滤波器与原始数据相比,SNR 提高了约两倍。BF 滤波图像的空间分辨率明显优于 MAF (MAF:9.5 mm,BF:6.8 mm)。在 MAF 滤波数据中,SUVmax 比原始数据低 24.1±9.9%,并且表现出强烈的尺寸依赖性。在 BF 滤波数据中,SUVmax 低 4.6±3.7%,并且没有观察到尺寸效应。
双边滤波允许在保持空间分辨率和防止小病变中 SUVmax 值平滑诱导低估的情况下,增加 PET 图像数据的 SNR。双边滤波似乎是标准平滑滤波器的一种有前途且优越的替代方法。