Extraction of primary signal from EPIDs using only forward convolution

A model is presented in which the scatter signal in images obtained by electronic portal imaging devices (EPIDs) is removed by a forward convolution method. The convolution kernel, k(t)(r) is a cylindrically symmetric kernel, generated by Monte Carlo, representing the scattered signal of a pencil beam at the image plane after the photons have gone through an object of thickness, t. A set of the kernels is presented and used to extract the primary signal. The signal from primary photons in the image, P(r), is extracted by an iterative method in which the essential assumption is that the scatter signal S(r) can be described by a superposition of the signal that would be obtained with the object removed from the beam, O(r), and the kernel, k(t)(r). The thickness, t, that is used to choose the kernel, is directly related to P(r) by a simple exponential relationship; hence the thickness, t, of the object and the primary signal, P(r), are both iterated to better estimates through this procedure. The model is tested on Monte Carlo simulated data, where the extracted primary signal is compared with the ''true'' primary signal. Results are presented for a set of phantoms of uniform thicknesses up to 35 cm, and for field areas up to 320 cm(2), and for an inhomogeneous phantom containing a sphere of a different density. The primary signal can be extracted to better than 1.5%, even when the original Scatter-to-Primary Ratio (SPR) is more than 25%. Finally, we have tested the model on EPID images, a nonuniform (breast) phantom is presented here. The breast phantom both have a curved external contour and contains a structure of a different density (lung). The radiological thickness of this breast phantom, as extracted using the above convolution model, was found to be within 2.8 mm (1 sd) of the true radiological thickness. (C) 1997 American Association of Physicists in Medicine.