Research On Enhancement Of The EPID Image

Electronic portal imaging system (electronic portal imaging device, EPID), is a newly-developed technology which is applied in portal positioning authentication to reduce the error of exposure. It is a real-time, digital positioning verification system, which can not only analyze the accuracy of portal shape, but also the accuracy of the patient's positioning, and it gradually becomes one of quality assurance tools in the radiation therapy. When conducting quantitative analysis of patient positioning, we usually take EPID image and the simulator film or digitally reconstructed image (DRR) generated by TPS for registration to get setup errors [1]. Then the preprocessing of the EPID image becomes particularly important, especially the high-energy EPID images for their low contrast.The article firstly gives a study on the traditional image enhancement methods employed in EPID software tools, such as histogram equalization, sharpening, Laplacian sharpening, and the unsharp masking based on the Laplacian sharpening. Then, based on retinal cortex theory, we can estimate the effective radiation image, and apply it to EPID image enhancement, removing the low contrast brought by too strong or too low X-ray. The two algorithms based on Retinex theory are: one is based on iterative global Retinex algorithm; the other, developing from the neurophysiology, is center-surround-based local Retinex algorithm. This paper takes advantage of the global Retinex algorithm put forward in literature [3] and Gaussian- environment-function-based multi-scale Retinex image enhancement algorithm defined by Jobson, analyses the core environmental function difference of Gaussian function in this multi-scale Retinex algorithm, the relationship between standard deviation of Gaussian function and the single-scale Retinex scale and the corresponding EPID image processing effects, and makes subjective and objective evaluation of its image-treatment. Finally, this author makes a preliminary study of the human visual system. The visual characteristics of the human's gray eyes can well explain the gray transformation results in the spatial domain, the understanding of which will in turn guide us in the gray transformation.