A Motion Compensation Approach for Oral and Maxillofacial Cone-beam Imaging

TL;DR

This paper presents an extension of a retrospective motion compensation method for cone-beam CT imaging, improving image quality by reducing motion artifacts through iterative estimation and correction, with validation on simulations, phantoms, and patient data.

Contribution

The study extends previous head CT motion compensation techniques to cone-beam CT, addressing field-of-view limitations and demonstrating clinical potential.

Findings

Significant reduction of motion artifacts in reconstructed images

Quantitative metrics confirm improved image sharpness

Expert assessment indicates clinical relevance of artifact suppression

Abstract

Purpose: Patient movement affects image quality in oral and maxillofacial cone-beam CT imaging. While many efforts are made to minimize the possibility of motion during a scan, relatively little attention has been given to motion compensation after the acquisition. Methods: In a previous study, we proposed a retrospective motion compensation approach for helical head CT imaging, which iteratively estimates and compensates for rigid head motion. This study reports on an extension of the previous method to cone-beam CT imaging. To address the issue of the limited field-of-view, improvements were made to the original method. The proposed motion estimation/ motion compensation (ME/MC) method was evaluated with simulations, phantom and patient studies. Two experts in dentomaxillofacial radiology assessed the diagnostic importance of the achieved motion artifact suppression. Results: The quality of the reconstructed images was improved after motion compensation, and most of the image artifacts were eliminated. Quantitative analysis by comparison to a reference image (simulation and phantom) and by calculation of a sharpness metric agreed with the qualitative observation. Conclusions: The proposed method has the potential to be clinically applied.