Quality evaluation for metal influenced CT data

In Computed Tomography (CT) metal objects in the region of interest introduce data inconsistencies during acquisition. The reconstruction process results in an image with star shaped artifacts. To enhance image quality the influence of metal objects can be reduced by different metal artifact reduction (MAR) strategies. For an adequate evaluation of new MAR approaches a ground truth reference data set is needed. In technical evaluations, where phantoms are available with and without metal inserts, ground truth data can easily be acquired by a reference scan. Obviously, this is not possible for clinical data. In this work, three different evaluation methods for metal artifacts as well as comparison of MAR methods without the need of an acquired reference data set will be presented and compared. The first metric is based on image contrast; a second approach involves the filtered gradient information of the image, and the third method uses a forward projection of the reconstructed image followed by a comparison with the actually measured projection data. All evaluation techniques are performed on phantom and on clinical CT data with and without MAR and compared with reference-based evaluation methods as well as expert-based classifications.