Metal artifact correction for x-ray computed tomography using kV and selective MV imaging
Meng Wu1, Andreas Keil2, Dragos Constantin3
1Department of Electrical Engineering, Stanford University, Stanford, California 94305.
Medical Physics
|December 5, 2014
Summary
This study improves computed tomography (CT) image quality for patients with metal implants by combining kilovoltage (kV) and megavoltage (MV) data. This dual-energy approach reduces metal streak artifacts and restores soft-tissue contrast, enhancing diagnostic accuracy.
Area of Science:
- Medical Imaging
- Radiotherapy Physics
Background:
- Computed tomography (CT) imaging is challenged by metal artifacts from implants or fillings.
- Photon starvation in kilovoltage (kV) CT data leads to significant image quality degradation in metal artifact regions.
Purpose of the Study:
- To enhance CT image quality for patients with metal implants by integrating kilovoltage (kV) and megavoltage (MV) projection data.
- To mitigate metal streak artifacts and restore soft-tissue contrast in CT images.
Main Methods:
- Developed and compared three image reconstruction methods: two filtered back-projection (FBP)-based analytic methods and one iterative method.
- Analytic methods involved patching modified MV data onto kV projections for FBP reconstruction.
- Iterative reconstruction utilized dual-energy (DE) penalized weighted least-squares (PWLS) to combine kV/MV data simultaneously.
Main Results:
- Dual-energy sinogram patch FBP and modified DE PWLS methods successfully suppressed metal streak artifacts.
- Restored information lost due to photon starvation in kV projections.
- Combined kV/MV images showed 10-15 HU lower RMSE for soft-tissue patterns and 5-10% improved structural similarity compared to kV-only images.
Conclusions:
- Combining kV and MV CT data effectively improves image quality in the presence of metal implants.
- The developed dual-energy reconstruction methods successfully address metal streak artifacts and photon starvation.
- Enhanced CT images facilitate improved delineation of structures for patients with metallic dental or orthopedic implants.
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