Pixelwise fusion for optimizing SNR in multiple-plate computed radiography imaging

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Abstract
The computed radiography (CR) technique, also known as the storage phosphor imaging technique, has evolved to be a major candidate for large-scale implementation of digital radiography during the past decade. In order to obtain a reasonable spatial resolution, the storage phosphor plate used is generally limited in thickness. This leads to X rays being only partially absorbed by the detector. Useful information may be contained in the X rays transmitted through the detector. Multiple-plate imaging techniques may be used to capture and utilize the X rays more efficiently. In this paper, an image fusion method, based on the Rayleigh principle and the Karhunen-Loeve (K-L) transform, is presented for optimizing the signal-to-noise ratio (SNR) of the fused image on a pixel-by-pixel basis. Because the multiple-plate images contain the same structural information, the signal components of the images are highly correlated with one another. Thus, the K-L transform is applied to decompose each of the multiple-plate images into an eigen image (the estimated signal) and a residual image (the estimated noise). An average representation entropy measure is maximized for selecting the number of eigen components to be included in the signal estimation. An experimental study, using an anthropomorphic chest phantom, is presented to illustrate pixelwise fusion of multiple-plate images. Experimental results show that the SNR of the fused image was improved by 12-48%, depending upon the anatomical regions of interest in the image.