ABSTRACT
@#Introduction: Metal artifacts can degrade the image quality of computed tomography (CT) images which lead to errors in diagnosis. This study aims to evaluate the performance of Laplace interpolation (LI) method for metal artifacts reduction (MAR) in CT images in comparison with cubic spline (CS) interpolation. Methods: In this study, the proposed MAR algorithm was developed using MATLAB platform. Firstly, the virtual sinogram was acquired from CT image using Radon transform function. Then, dual-adaptive thresholding detected and segmented the metal part within the CT sinogram. Performance of the two interpolation methods to replace the missing part of segmented sinogram were evaluated. The interpolated sinogram was reconstructed, prior to image fusion to obtain the final corrected image. The qualitative and quantitative evaluations were performed on the corrected CT images (both phantom and clinical images) to evaluate the effectiveness of the proposed MAR technique. Results: From the findings, LI method had successfully replaced the missing data on both simple and complex thresholded sinogram as compared to CS method (p-value = 0.17). The artifact index was significantly reduced by LI method (p-value = 0.02). For qualitative analysis, the mean scores by radiologists for LI-corrected images were higher than original image and CS-corrected images. Conclusion: In conclusion, LI method for MAR produced better results as compared to CS interpolation method, as it worked more effective by successfully interpolated all the missing data within sinogram in most of the CT images.
ABSTRACT
@#Introduction: In medical physics applications, effective atomic numbers are often employed to set apart and specify the interaction of ionizing radiation with matter. Methods: The effective atomic number of soy-lignin bonded with Rhizophora spp. particleboards were analyzed using Energy Dispersive X-ray analysis and Carbon Hydrogen Nitrogen Analyzer. The effective atomic number were compared and recorded with reference to the effective atomic value of water. Results: The result showed that the effective atomic number calculated for adhesive bound Rhizophora spp. samples were close to effective atomic value of water, with 3.34 – 3.47 % differences by using Energy Dispersive X-ray and 6.47 – 6.78 % differences by using Carbon Hydrogen Nitrogen analysis. The result revealed that through Energy Dispersive X-ray method, the effective atomic number was much closer to water compared to Carbon Hydrogen Nitrogen analysis. Conclusion: Despite the availability of hydrogen content in the samples in Carbon Hydrogen Nitrogen analysis, Energy Dispersive X-ray method was much more preferred and gave better result compared to Carbon Hydrogen Nitrogen analysis thus provide a compelling argument for the use of Energy Dispersive X-ray method to measure the effective atomic number of Rhizophora spp. particleboard in medical physics applications.