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The PCA filtered image is much closer to the noiseless image than the unfiltered image. The image SNR improves by a factor of 3.8��0.6. Higher image quality allows for better visualization of the temporal pO2 fluctuations as can also be seen in Figure 6. PCA filtering of projections produces a greater improvement in projection SNR compared to the improvement in image SNR. This results from processing/filtering of the projections during reconstruction (e.g., high-frequency noise in the projections is filtered by the half-Nyquist frequency cutoff in the filtered backprojection). This filtering has a more appreciable effect on the unfiltered projections than on the PCA filtered projections and subsequently brings the SNR of unfiltered images closer to that of PCA filtered images. Similar simulations were done with two and three differently oscillating http://www.selleckchem.com/products/BIBF1120.html volumes, with three and four PCs used for the PCA approximation, respectively. Adding more PCs ensures that the oscillation patterns from different volumes are reconstructed properly, but includes more noise. Therefore, while SNR is enhanced, the improvement diminishes when more PCs are required for an accurate approximation. Table 1 summarizes the effectiveness of using PCA approximation as a noise filter for different numbers of oscillating volumes. Since the method of calculating SNR depends on absolute signal amplitude and weighting and/or normalization http://www.selleck.cn/products/carfilzomib-pr-171.html processes occur during image reconstruction, direct comparisons between the columns of Table 1 should not be made. Simulations were also used to determine how PCA filtering performance depends on the relative size/weight of the volume exhibiting the temporal pattern of interest. The digital phantom consisted of an outer cube with sides 20 voxels in length and a smaller cube of varying size centered inside exhibiting sinusoidal temporal pO2 fluctuations. The results of these simulations are shown in Figure 7. The unfiltered data has SNR http://www.selleckchem.com/products/Metformin-hydrochloride(Glucophage).html filtering converges to that without filtering. Simulations were used to determine how PCA filtering affects image resolution by looking at the reproduction of edges in an image. Ideally, intensity values along a line perpendicular to an edge would follow a step function. In reality, the finite resolution of the imaging system results in blurring, causing intensity values along a line perpendicular to an edge to become sigmoidal. The amount of deviation from a step function is related to the image resolution.