Universal orbit design for metal artifact elimination

Abstract

Abstract Objective. Metal artifacts are a persistent problem in CT and cone-beam CT. In this work, we propose to reduce or even eliminate metal artifacts by providing better sampling of data using non-circular orbits. Approach. We treat any measurements intersecting metal as missing data, and aim to design a universal orbit that can generally accommodate arbitrary metal shapes and locations. We adapted a local sampling completeness metric based on Tuy’s condition to quantify the extent of sampling in the presence of metal. A maxi-min objective over all possible metal locations was used for orbit design. A simple class of sinusoidal orbits was evaluated as a function of frequencies, maximum tilt angles, and orbital extents. Experimental implementation of these orbits were performed on an imaging bench and evaluated on two phantoms, one containing metal balls and the other containing a pedicle screw assembly for spine fixation. Metal artifact reduction (MAR) performance was compared amongst three approaches: non-circular orbits only, algorithmic correction only, and a combined approach. Main results. Theoretical evaluations of the objective favor sinusoidal orbits with large tilt angles and large orbital extents. Furthermore, orbits that leverage redundant azimuthal angles to sample non-redundant data have better performance, e.g. even or non-integer frequency sinusoids for a 360° acquisition. Experimental data support the trends observed in theoretical evaluations. Reconstructions using even or non-integer frequency orbits present less streaking artifacts and background details with finer resolution, even when multiple metal objects are present and even in the absence of MAR algorithms. The combined approach of non-circular orbits and MAR algorithm yields the best performance. The observed trend in image quality is supported by quantitative measures of sampling and severity of streaking artifact. Significance. This work demonstrates that sinusoidal orbits are generally robust against metal artifacts and can provide an avenue for improved image quality in interventional imaging.