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Figure 1 | BMC Medical Physics

Figure 1

From: The 2D Hotelling filter - a quantitative noise-reducing principal-component filter for dynamic PET data, with applications in patient dose reduction

Figure 1

Bias for varying percent blood pixels. A) 2D Hotelling filtered data (PC1-4) gives increasing summed bias with increasing blood fraction (top curve). The statistical fluctuations in the summed bias, for non-filtered data, display no correlation with blood fraction (horizontal lower line). Excluding the frame with only blood activity prior to performing the Hotelling filter reduces the summed bias close to that of 0% blood (see arrow at 33%). B) remaining noise in ROIs of simulated data, rs, as a function of number n of employed principal components in the 2D Hotelling filter. C) summed bias for varying number of principal components (n=largest principal component remaining in the Hotelling filter process).

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BMC Medical Physics

ISSN: 1756-6649