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PDS-MAR: a fine-grained projection-domain segmentation-based metal artifact reduction method for intraoperative CBCT images with guidewires

Tianling Lyu, Zhan Wu, Gege Ma, Chen Jiang, Xinyun Zhong, Yan Xi, Yang Chen, Wentao Zhu

发表年份
2023
引用次数
17

摘要

Abstract Objective. Since the invention of modern Computed Tomography (CT) systems, metal artifacts have been a persistent problem. Due to increased scattering, amplified noise, and limited-angle projection data collection, it is more difficult to suppress metal artifacts in cone-beam CT, limiting its use in human- and robot-assisted spine surgeries where metallic guidewires and screws are commonly used. Approach. To solve this problem, we present a fine-grained projection-domain segmentation-based metal artifact reduction (MAR) method termed PDS-MAR, in which metal traces are augmented and segmented in the projection domain before being inpainted using triangular interpolation. In addition, a metal reconstruction phase is proposed to restore metal areas in the image domain. Main results. The proposed method is tested on both digital phantom data and real scanned cone-beam computed tomography (CBCT) data. It achieves much-improved quantitative results in both metal segmentation and artifact reduction in our phantom study. The results on real scanned data also show the superiority of this method. Significance. The concept of projection-domain metal segmentation would advance MAR techniques in CBCT and has the potential to push forward the use of intraoperative CBCT in human-handed and robotic-assisted minimal invasive spine surgeries.

关键词

Computer visionArtificial intelligenceArtifact (error)Imaging phantomProjection (relational algebra)Computer scienceSegmentationCone beam computed tomographyReduction (mathematics)Nuclear medicine

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