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Metal Artifact Reduction: A Problem of Tremendous Importance in Medical Imaging
Abstract
Metallic implants are known to generate bright and dark streaking artifacts in x-ray computed tomography (CT) images. These artifacts cause loss of information, reduces the resolution, forms noise which hinders diagnostic capability. The reduction of metal artifact is of immense importance in the present scenario. We propose seeded watershed segmentation-interpolation based sinogram correction method to reduce the metal artifacts caused by metallic implants. We tend to find projection bins affected by the metallic objects in the raw projection data and to replace the corrupted values by appropriate estimates. The novelty of proposed method lies in segmentation of metal part from the CT image by seeded watershed segmentation method, using IlastiK tool. Proposed method is experimented using dataset pertaining to different clinical cases. Solution is studied for correctness by quantitatively as well as qualitatively. The result presents significant improvement in artifact reduction aiding to better diagnostic ability.
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