Reducing metal artifacts by restricting negative pixels.

Area of Science:

• Medical Imaging
• Computational Imaging
• Materials Science

Background:

• X-ray computed tomography (CT) images are often degraded by streaking artifacts when imaging metallic objects.
• These artifacts stem primarily from X-ray beam hardening effects, leading to inaccurate measurements.
• A notable characteristic of these artifacts is the frequent appearance of negative pixel values in affected regions.

Purpose of the Study:

• To develop and validate a novel objective function and iterative algorithm for reducing metal artifacts in CT images.
• To address the limitations of simple thresholding methods (e.g., setting negative values to zero).
• To improve the quality of CT reconstructions in the presence of metallic objects.

Main Methods:

• An objective function was formulated to constrain negative pixel values within the CT image.
• A novel iterative algorithm was proposed to optimize this objective function, estimating metal-affected projections.
• The filtered backprojection algorithm was employed for final image reconstruction using the corrected projections.

Main Results:

• The proposed iterative algorithm effectively reduced metal artifacts in X-ray CT images.
• The method demonstrated superior performance compared to naive approaches like zeroing negative pixel values.
• Successful application to airport baggage CT scans containing metallic objects was shown.

Conclusions:

• The developed objective function and iterative algorithm offer an effective solution for metal artifact reduction in CT imaging.
• This approach enhances the diagnostic quality of CT scans by mitigating beam hardening-induced artifacts.
• The findings have significant implications for security screening and other applications involving CT of metallic components.