Purpose: Computed tomography (CT) streak artifacts caused by metallic implants remain a challenge for the automatic processing of image data. The impact of metal artifacts in the soft-tissue region is magnified in cone-beam CT (CBCT), because the soft-tissue contrast is usually lower in CBCT images. The goal of this study was to develop an effective offline processing technique to minimize the effect.
Methods and materials: The geometry calibration cue of the CBCT system was used to track the position of the metal object in projection views. The three-dimensional (3D) representation of the object can be established from only two user-selected viewing angles. The position of the shadowed region in other views can be tracked by projecting the 3D coordinates of the object. Automatic image segmentation was used followed by a Laplacian diffusion method to replace the pixels inside the metal object with the boundary pixels. The modified projection data were then used to reconstruct a new CBCT image. The procedure was tested in phantoms, prostate cancer patients with implanted gold markers and metal prosthesis, and a head-and-neck patient with dental amalgam in the teeth.
Results: Both phantom and patient studies demonstrated that the procedure was able to minimize the metal artifacts. Soft-tissue visibility was improved near or away from the metal object. The processing time was 1-2 s per projection.
Conclusion: We have implemented an effective metal artifact-suppressing algorithm to improve the quality of CBCT images.