Estimating the Center of Rotation of Tomographic Imaging Systems with Limited Projections
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For a tomographic imaging system, image reconstruction quality is highly correlated with accurate determination of the true center of rotation (COR) location. A significant center offset error will introduce ringing, streaking, or other artifacts into the reconstruction, while smaller COR error will cause blurring of the image. Well known COR correction techniques including image registration, center of mass calculation, or reconstruction evaluation work well under certain conditions. However, some conditions, e.g. parallel projections or no tilt in the sensor plane, are often violated in practical situations. Furthermore, limited projections will introduce extra stripe artifacts into the reconstruction that reduce the effectiveness of many COR correction techniques that are sensitive to noise. In this paper, we propose a revised variance-based algorithm to find the correct COR position automatically. The algorithm was tested on phantom and actual cases separately, and the results show improved performance.