Improved Metal Artifact Reduction via Image Quality Metric Optimization

Michael Manhart, Marios Psychogios, Nadine Amelung, Michael Knauth, Christopher Rohkohl


Published in:Fully3D 2017 Proceedings


Cone-beam CT images acquired with C-arm systems are frequently disturbed by metal artifacts. Recently, correction algorithms based on the normalized metal artifact reduction (NMAR) algorithm were introduced for commercial C-arm systems enabling restoration of most part of soft tissue contrast. The NMAR algorithm replaces attenuation values of rays passing through metal by interpolation in projection domain. Since interpolation is imperfect and can cause inconsistencies, residual streak and shadow artifacts are often visible even after NMAR reconstruction. We introduce a novel iterative post-processing step for the NMAR algorithm which modifies the interpolated attenuation values by optimizing an image quality metric in the reconstructed volume to reduce residual artifacts. The novel approach was able to reduce residual artifacts on all 14 evaluated clinical neuroradiology datasets with only moderate increase of computation time (average +12 s).
Michael Manhart
Siemens Healthcare GmbH, Germany
Marios Psychogios
Universitätsmedizin Göttingen, Germany
Nadine Amelung
Universitätsmedizin Göttingen, Germany
Michael Knauth
Universitätsmedizin Göttingen, Germany
Christopher Rohkohl
Siemens Healthcare GmbH, Germany
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