A novel forward projection-based metal artifact reduction method for flat-detector computed tomography

Abstract

Metallic implants generate streak-like artifacts in flat-detector computed tomography (FD-CT) reconstructed volumetric images. This study presents a novel method for reducing these disturbing artifacts by inserting discarded information into the original rawdata using a three-step correction procedure and working directly with each detector element. Computation times are minimized by completely implementing the correction process on graphics processing units (GPUs). First, the original volume is corrected using a three-dimensional interpolation scheme in the rawdata domain, followed by a second reconstruction. This metal artifact-reduced volume is then segmented into three materials, i.e. air, soft-tissue and bone, using a threshold-based algorithm. Subsequently, a forward projection of the obtained tissue-class model substitutes the missing or corrupted attenuation values directly for each flat detector element that contains attenuation values corresponding to metal parts, followed by a final reconstruction. Experiments using tissue-equivalent phantoms showed a significant reduction of metal artifacts (deviations of CT values after correction compared to measurements without metallic inserts reduced typically to below 20 HU, differences in image noise to below 5 HU) caused by the implants and no significant resolution losses even in areas close to the inserts. To cover a variety of different cases, cadaver measurements and clinical images in the knee, head and spine region were used to investigate the effectiveness and applicability of our method. A comparison to a three-dimensional interpolation correction showed that the new approach outperformed interpolation schemes. Correction times are minimized, and initial and corrected images are made available at almost the same time (12.7 s for the initial reconstruction, 46.2 s for the final corrected image compared to 114.1 s and 355.1 s on central processing units (CPUs)).

Artifact Reduction of Different Metallic Implants in Flat Detector C-Arm CT

“…These artifacts may be the secondary artifacts introduced by the correction scheme and may be the reason the imaging quality remained inferior to that of native images. 15,16 In our results, the types of metal objects and the coil lengths did not affect the results of the investigated MAR algorithm. In assessing subjective image quality, we demonstrated that the MAR software substantially improved the visibility of the metal object vicinity, in which image qualities were most severely degraded before correction.…”

Artefacts in CBCT: a review

“…Consequently, no absorption can be computed and severe artefacts are induced as these zero entries are backprojected into the volume. 30 …”

Evaluation of a Metal Artifacts Reduction Algorithm Applied to Postinterventional Flat Panel Detector CT Imaging

“…The MAR prototype algorithm (Fig 1) investigated is a modification and extension of the procedure first published by Prell et al 4 The MAR reconstructions were performed on an off-line prototype research workstation (Siemens). The algorithm consists of several steps.…”

“…One of the first interpolationbased MAR algorithms used a 1D linear interpolation for singlerow CT data, which is inadequate for FDCT data. 3 The MAR algorithm investigated in this work, developed by Siemens Healthcare Sector, is a modification and extension of a recently published MAR procedure by Prell et al 4 We present validation of the FDCT MAR prototype algorithm by using a phantom study and an objective critique by 7 clinicians.…”