Evaluation of metal artefact reduction using dual-step adaptive thresholding technique in computed tomography

• Main Author: Hassan, Mohd Norsyafi
• Format: Thesis
• Language: English
• Published: 2018
• Subjects: R Medicine (General)
• Online Access: http://eprints.usm.my/46511/1/Dr.%20Mohd%20Norsyafi%20Hassan-24%20pages.pdf; http://eprints.usm.my/46511/

Background: Metal objects present in CT images may give rise to streak artefact. In the presence of severe artefacts, image quality may be extensively degraded and important clinical findings and pathology in the vicinity of the metal objects may be obscured. The purpose of this study is to evaluate the effectiveness of the dual-step adaptive thresholding technique as a method of metal artefact reduction in CT studies. Methodology: A total of 14 CT studies which contained metal-induced artefacts resulted from various surgical implants were retrieved from the Picture Archive Communication System (PACS). The CT images were corrected using the DSAT algorithm in MATLAB workspace to generate the artefact-corrected images with acceptable quality. Both groups of original images and artefact-corrected images were evaluated quantitatively using noise and SNR and qualitatively using visual evaluation by 2 evaluators. Level of significance was determined (p < 0.05). Results: A significant reduction of the noise were noticed in the corrected CT images following DSAT technique for metal artefact correction with the mean noise of 14.576 ± 11.7 as compared to the original images with mean of 40.177 ± 23.785 (p < 0.0005). A significant improvement of SNR was also demonstrated following DSAT correction with the mean SNR of 3.877 ± 3.931 for the corrected images in comparison to 3.614 ± 2.839 for the original images (p = 0.017). Visual evaluation has demonstrated reduced appearance of metal artefacts with increased conspicuity of adjacent structures (p < 0.05). Conclusion: Metal artefact correction using dual-step adaptive thresholding technique has the ability to suppress metal-induced artefacts with significant improvement of image quality.