Ring Artifacts Correction Based on Global–Local Feature Interaction Guidance in the Projection Domain

Ring artifacts frequently arise in CT imaging due to the inconsistent responses of detector units to X-rays. This effect is further exacerbated in photon-counting detectors, resulting in stripe artifacts in the sinogram. Under circular scanning, such artifacts manifest as concentric ring artifacts radiating from the center of rotation, severely degrading image quality. Based on the properties of the Radon transform and the inherent ray conjugacy in fan-beam CT systems, ideal sinograms exhibit smoothness and global correlation. Influenced by various physical factors and object properties during practical data acquisition, stripe artifacts exhibit localized high-frequency characteristics along both the detector and angular directions, with their intensities correlated with the projection values. Therefore, we propose a ring artifacts correction method based on the interaction guidance between global and local features in the projection domain. Applying the discrete wavelet transform, the sinogram is decomposed into low-frequency sub-bands that predominantly capture global feature and high-frequency sub-bands that primarily represent local feature, each corrected independently. To address the challenge of decoupling global and local feature within the sub-band images, we propose a global-local feature interaction guidance module to achieve precise correction of stripe artifacts. Extensive experimental results demonstrate that the proposed method consistently outperforms existing approaches in quantitative metrics and visual artifacts suppression, highlighting its robustness and clinical applicability.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Instrumentation and Measurement
Published
2025-01-01
DOI
https://doi.org/10.1109/tim.2025.3612561
Primary Topic
Image Processing and 3D Reconstruction
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ring Artifacts Correction Based on Global–Local Feature Interaction Guidance in the Projection Domain

Yunze Liu, Xing Zhao, Ping Yang, Ligen Shi et al.
IEEE Transactions on Instrumentation and Measurement
Image Processing and 3D Reconstruction
article

Ring Artifacts Correction Based on Global–Local Feature Interaction Guidance in the Projection Domain

Yunze Liu, Xing Zhao, Ping Yang, Ligen Shi, C.C. Su
article en

Abstract

Ring artifacts frequently arise in CT imaging due to the inconsistent responses of detector units to X-rays. This effect is further exacerbated in photon-counting detectors, resulting in stripe artifacts in the sinogram. Under circular scanning, such artifacts manifest as concentric ring artifacts radiating from the center of rotation, severely degrading image quality. Based on the properties of the Radon transform and the inherent ray conjugacy in fan-beam CT systems, ideal sinograms exhibit smoothness and global correlation. Influenced by various physical factors and object properties during practical data acquisition, stripe artifacts exhibit localized high-frequency characteristics along both the detector and angular directions, with their intensities correlated with the projection values. Therefore, we propose a ring artifacts correction method based on the interaction guidance between global and local features in the projection domain. Applying the discrete wavelet transform, the sinogram is decomposed into low-frequency sub-bands that predominantly capture global feature and high-frequency sub-bands that primarily represent local feature, each corrected independently. To address the challenge of decoupling global and local feature within the sub-band images, we propose a global-local feature interaction guidance module to achieve precise correction of stripe artifacts. Extensive experimental results demonstrate that the proposed method consistently outperforms existing approaches in quantitative metrics and visual artifacts suppression, highlighting its robustness and clinical applicability.

IEEE Transactions on Instrumentation and MeasurementVol. 74
Capital Normal University (CN), Tsinghua University (CN)
Openalex Percentile: Top 74%
Image Processing and 3D Reconstruction
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.