Evaluation of dual-front active contour segmentation and metal shadow filling methods on metal artifact reduction in multi-slice helical CT

A novel metal artifact reduction strategy including projection reformation, metal region segmentation, and metal shadow filling was proposed. Both metal region segmentation and shadow filling are critical steps to assure good artifact suppression results. This preliminary study evaluated the performance of two segmentation methods and three region filling methods on metal artifact reduction of clinical cases. Gradient-based threshold method (GBT) and dual-front active contour model-based method (DFAC) were utilized to segment metal implants from reformatted projections, Delaunay triangulation-based (DTB), anisotropic diffusion-based, and exemplar-based, interpolation methods were utilized to fill the metal shadows, respectively. The image quality was evaluated by a radiologist in terms of visual conspicuity of the bladder base, prostate, and rectum. Overall, the image quality and the conspicuity in some critical organs were significantly improved for all corrections. Compared to the GBT method, the DFAC method had more accurate segmentation, which resulted in better artifact suppression. The interpolation process does not guarantee the data consistency among projection views, which can introduce additional artifacts, especially for large metal objects. Although the DTB method produced the smoothest metal shadow interpolation results, which is considered the worst scenario according to the criterion of image restoration, it induced the least additional artifacts to the reconstructed images compared to the other two structure-saving methods. As such, region interpolation methods should follow the criterion to generate metal shadow data consistent with the CT acquisition geometry, which might be quite different from the general standard of image restoration in computer vision and image processing.