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Related Experiment Video

Updated: Feb 8, 2026

Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization

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Two methods for reducing moving metal artifacts in cone-beam CT.

Andreas Hahn^1,2, Michael Knaup¹, Marcus Brehm³

¹Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.

Medical Physics

|June 26, 2018

Summary

This summary is machine-generated.

Two new methods, MMAR and MoCoMAR, effectively reduce metal artifacts in cone-beam CT scans caused by moving fiducial markers. These advanced techniques outperform standard methods, improving image quality in radiation therapy.

Keywords:

Cone-beam CT image-guided radiation therapy moving metal artifact reduction sinogram inpainting

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Area of Science:

Medical Imaging
Radiation Oncology
Image Processing

Background:

Fiducial markers used in image-guided radiation therapy can cause streak artifacts in cone-beam CT (CBCT) scans.
Standard metal artifact reduction (MAR) methods struggle with artifacts from large motion of these markers.
Effective artifact reduction is crucial for accurate tumor localization and treatment planning.

Purpose of the Study:

To introduce and evaluate two novel methods, MMAR and MoCoMAR, for reducing CBCT artifacts caused by moving metal inserts.
To compare the performance of MMAR and MoCoMAR against a standard MAR method (MAR1).

Main Methods:

MMAR: Utilizes coarse metal segmentation in the image domain and refined segmentation in the raw data domain with linear interpolation.
MoCoMAR: Employs motion compensation (MoCo) to obtain motion-free volumes, followed by normalized metal artifact reduction (NMAR).
Both methods were tested on patient CBCT data from thorax/abdomen and a 4D thorax simulation.

Main Results:

MMAR and MoCoMAR successfully removed all artifacts originating from moving metal inserts in both patient data and simulations.
Both novel methods significantly outperformed the standard MAR1, which was ineffective for metal inserts with significant motion.
MMAR and MoCoMAR demonstrated superior artifact reduction capabilities compared to existing techniques.

Conclusions:

Two effective methods, MMAR and MoCoMAR, were developed to address artifacts from moving metal inserts in CBCT.
Both methods showed excellent performance on simulations and patient cases.
MMAR is suitable for general use, while MoCoMAR is more computationally intensive and offers benefits primarily when motion-compensated images are also required.