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Efficient extended field of view (eFOV) reconstruction techniques for multi-slice helical CT

Truncation of CT projection data is always coupled with incomplete angular sampling and can lead to severe image artifacts in clinical CT. Extrapolation of projection data is needed to restore CT values inside and outside the scan field of view (SFOV). We present three types of extrapolation schemes. The first type (M1) is characterized by extrapolation of projection data using a virtual object of constant attenuation. For multi-slice helical CT this extrapolation scheme is applied in a row-wise manner. The second type (M2) utilizes consistency conditions of parallel projection data. The conservation of mth order moments of non-truncated projections can be utilized for the extrapolation of truncated projection data by fitting extrapolation functions of variable length. The third method (M3) extrapolates truncated data by sinogram decomposition and completion. For each voxel in image space the corresponding trace in the 3D-sinogram is computed. The minimum signal within each trace is extrapolated to the extended sinogram parts, which represent the extended FOV. Based on the evaluation of both simulation data of an anthropomorphic thorax phantom and clinical data, we evaluate the three reconstruction techniques. Sinogram decomposition proofs to be better than the other techniques, but is computationally very demanding.