Abstract: In computed tomography (CT) imaging of C/C composite materials, one of the main challenges is the presence of significant ring artifacts in the reconstructed image. These artifacts are primarily caused by the non-linear and non-uniform response of the detector, which hinders the accurate detection and evaluation of defects in the inspected components. To overcome this issue, a novel physical correction method based on the underlying detector response mechanism was proposed in this work. The key idea behind the proposed method is to take advantage of the homogeneous composition and uniform density of C/C composite materials. Firstly, a pre-reconstruction process was conducted to locate the shape and position of C/C components utilizing the degraded projection data. Moreover, a threshold segmentation technique was employed to extract a detailed and accurate three-dimensional model of the inspected C/C components. By performing forward projection on the segmented three-dimensional model of the inspected C/C components, theoretical projection data of homogeneous components could be obtained. The next step involved combining the available information about the material and density to carry out a re-projection procedure. This analysis enables the establishment of a robust mapping relationship between the theoretical and measured values of the projection data, which is then employed to correct for the detector response by a polynomial fitting procedure. Finally, the corrected projection data was used to reconstructed the optimized CT images of which ring artifacts would be significantly suppressed. Comparing with conventional low-pass filter based methods for addressing ring artifacts, this approach takes into account the physical causes of these artifacts while making full use of the prior knowledge regarding the inspected object. Not only does it effectively reduce the presence of ring artifacts, but it also significantly retains the texture and details of the original CT images. By eliminating the interference caused by these artifacts, the method enhances the detection system’s ability to identify and evaluate defects accurately. Consequently, this technique provides a valuable theoretical foundation for improving the defect detection capabilities of CT inspection systems for C/C components. It successfully addresses the challenges posed by ring artifacts by considering their physical origins and leveraging the prior knowledge about the inspected object. The results of the study demonstrate its effectiveness in reducing ring artifacts, enhancing image quality, and eliminating interference during defect identification. Moving forward, this method holds great potential for further improving the performance and reliability of CT inspection systems for C/C components.