Novel statistical analysis of two sources of digital chest radiographs
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Statistical estimation techniques for medical images require well-founded models for the data formation and acquisition process. In our work, we attempt to quantify the appropriate empirical noise model for two alternative digital chest radiography modalities. In this study, we acquired image sets from the same clinical x-ray unit using photostimulable phosphor plates (PPP) and film/screen. The images were acquired in the range of 1-9 mR. The PPP data, at 1760 by 2140 pixels, were transferred directly to our workstations for analysis, and the films were digitized at 2048 by 2480 pixels (0.2 mm resolution for both modalities). 1024 by 1024 regions of interest (ROIs) without edge effects or artifacts were then extracted. Using Fourier transform methods, the noise power spectra were formed for all the images with smoothing applied near the axes to exclude frequency components due to beam profile, detector inhomogeneity and other structural noise. The noise power spectra were then integrated to find the variance at the exposure in question. This corresponds to an estimate of the non-structural variance. The data for all images obtained with one method were finally combined to form the variance function (variance as a function of the mean) for the modality. The data show that for the range of exposure considered, the PPP and digitized film modalities exhibit significant differences in noise structure. Subtle differences in the noise power spectra were seen. Of particular interest to our application, however, the variance function in the two cases was seen to differ in its functional form. The data from the photostimulable phosphor plates correspond well to a linear model (variance proportional to the mean) throughout most of the range investigated, whereas the digitized film variance function corresponds better to a higher-degree polynomial fit over the range considered. This study indicates that separate models may be warranted for different sources of digital chest radiographs and also suggests the type of assumption that, based on empirical findings, may be useful in such a framework.
