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Deep scatter estimation for coarse anti-scatter grids as used in photon-counting CT

Due to the smaller detector pixels in photon-counting CT, coarse anti-scatter grids are used. This may lead to high frequencies in the scattered radiation and therefore moiré artifacts in the reconstructed images can occur. It has been shown that deep convolutional neural networks are very effective to correct scatter artifacts in clinical CT. In this work we present an adapted version of the deep scatter estimation (DSE) to correct for the high frequency artifacts effectively. With the use of DSE the mean absolute error of the scatter artifacts is reduced from about 8 HU to under 1 HU. At the same time the moiré artifacts can be prevented and additional post-processing in the image can be avoided.