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Normalized metal artifact reduction (NMAR) in computed tomography

Severe artifacts degrade the image quality and the diagnostic value of CT images if metal objects are present in the field of measurement. The standard method for metal artifact reduction (MAR) replaces affected projection data by interpolated data. Often, linear interpolation is used. However, sinogram interpolation introduces new artifacts and lacks accuracy close to metal objects even if more complex interpolation schemes are used. Recently, a method was presented, which uses a simple length normalization of the sinogram prior to interpolation in order to better preserve the contrast between air and water-equivalent objects. However, contrast between objects from different materials, water and bone, for example, is still impaired. We introduce a generalized normalization technique, which concisely preserves details of different materials. This normalization is performed based on a forward projection of a ternary image, which is obtained from a multi-threshold segmentation of the initial image. Simulations and measurements are performed to evaluate our normalized metal artifact reduction method (NMAR) in comparison to standard MAR with linear interpolation and MAR based on simple length normalization. We find considerable improvements in particular for bone structures with metal implants. The improvements are quantified by comparing profiles through images and sinograms for the different methods using simulated data. NMAR clearly outperforms both other methods. We also obtain promising results by applying NMAR to clinical data. This is demonstrated with a scan of a patient with two hip endoprostheses. NMAR is computationally inexpensive, as only parts of a forward projection need to be computed additional to the steps of a interpolation-based MAR. Therefore, our normalization technique can be used as an additional step in any conventional sinogram interpolation-based MAR method.