Metal Artifact Reduction in Cone-Beam X-Ray CT via Ray Profile Correction

TL;DR

This paper presents a data-driven metal artifact reduction algorithm for cone-beam X-ray CT that improves image quality in spine surgery by removing streaks and recovering hidden anatomical structures, aiding accurate diagnosis.

Contribution

The proposed method introduces a novel ray profile correction technique leveraging prior CT scans for effective metal artifact reduction in clinical spine surgery scenarios.

Findings

Successfully removed streak artifacts caused by metal implants.

Revealed anatomical structures obscured by artifacts.

Enhanced surgeon confidence in implant placement accuracy.

Abstract

In computed tomography (CT), metal implants increase the inconsistencies between the measured data and the linear attenuation assumption made by analytic CT reconstruction algorithms. The inconsistencies give rise to dark and bright bands and streaks in the reconstructed image, collectively called metal artifacts. These artifacts make it difficult for radiologists to render correct diagnostic decisions. We describe a data-driven metal artifact reduction (MAR) algorithm for image-guided spine surgery that applies to scenarios in which a prior CT scan of the patient is available. We tested the proposed method with two clinical datasets that were both obtained during spine surgery. Using the proposed method, we were not only able to remove the dark and bright streaks caused by the implanted screws but we also recovered the anatomical structures hidden by these artifacts. This results in an improved capability of surgeons to confirm the correctness of the implanted pedicle screw placements.