1. Using segmentation in CT metal artifact reduction
- Author
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Harry E. Martz, Seemeen Karimi, Christoph Wald, and Pamela C. Cosman
- Subjects
medicine.diagnostic_test ,Computer science ,business.industry ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Computed tomography ,Image segmentation ,Iterative reconstruction ,Mathematical morphology ,Reduction methods ,Reduction (complexity) ,Metal Artifact ,Engineering ,medicine ,Segmentation ,Computer vision ,Reconstructed image ,Artificial intelligence ,Projection (set theory) ,business ,Interpolation - Abstract
Metal artifact reduction methods in computed tomography replace the projection data passing through metals with an estimate of the true data. Inaccurate estimation leads to the generation of secondary artifacts. Data estimates can be improved by the use of prior knowledge of the projection data. In this paper, a method has been created to generate a prior image. The method uses computer vision techniques to segment regions of the initially reconstructed image and then discriminates between regions that are likely to be artifacts and anatomical structures. Results on test images show that metal artifacts are reduced and that few secondary artifacts are present, even in the case of multiple metal objects.
- Published
- 2012
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