Suitability of bilateral filtering for edge-preserving noise reduction in PET

Abstract

BackgroundTo 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.MethodsData 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.ResultsWith 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.ConclusionBilateral 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.

Combining multiple FDG‐PET radiotherapy target segmentation methods to reduce the effect of variable performance of individual segmentation methods

“…[32][33][34] For the gradient-based method a 7-mm bilateral filter was applied and the deblurring step was accomplished with 30 iterations of Landweber's algorithm with a symmetrical 6 mm FWHM point spread function (PSF) in accordance with Geets et al 14 The choice of a 7-mm bilateral filter was based on the method outlined by Hofheinz et al 35 as it provides comparable signal-to-noise in background regions to the 5 mm Gaussian filter used for the other segmentation methods.…”

Correction of quantification errors in pelvic and spinal lesions caused by ignoring higher photon attenuation of bone in [18F]NaF PET/MR

“…The algorithm that automatically subtracts the bladder is explained in the Appendix. Before the bone structure delineation, all PET image volumes were smoothed with an edge-preserving bilateral filter 25 with a spatial standard deviation of 8.5 mm and an intensity width of SUV = 2.5 to lower the noise.…”

On the Reliability of Automatic Volume Delineation in Low-Contrast [18F]FMISO-PET Imaging

“…Accordingly, FDG PET images show an image contrast about one order of magnitude higher than when using FMISO (Abolmaali et al 2011). Improvements of FMISO-PET image quality may be obtained by the following: 1) using new scanner technology such as improved detectors (Yasuda et al 2013), 2) introduction of signal improving algorithms (Hofheinz et al 2011), 3) developing imaging protocols producing data sets with the best achievable contrast (Abolmaali et al 2011) and 4) methods for partial volume correction (Hofheinz et al 2012). However, reliable target volume delineation is a prerequisite.…”