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Elimination of biological and physical artifacts in abdomen and brain computed tomography procedures using filtering techniques
Authors:Hiba Omer  Nissren Tamam  Suhaib Alameen  Sahar Algadi  Duong Thanh Tai  Abdelmoneim Sulieman
Institution:1. Department of Basic Sciences, Deanship of Preparatory Year and Supporting Studies, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 34212, Saudi Arabia;2. Physics Department, College of Sciences, Princess Nourah bint Abdulrahman University, P.O Box 84428, Riyadh 11671, Saudi Arabia;3. Sudan University of Science and Technology, College of Medical Radiologic Science, P.O.Box 1908, Khartoum, Sudan;4. Department of Basic Sciences, Deanship of Preparatory Year and Supporting Studies, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 34212, Saudi Arabia;5. Department of Industrial Electronics and Biomedical Engineering, HCMC University of Technology and Education, Ho Chi Minh 749000, Vietnam;6. Prince Sattam Bin Abdulaziz University, College of Applied Medical Sciences, Radiology and Medical Imaging Department, PO Box 422, Alkharj 11942, Saudi Arabia;7. Basic Science Department, College of Medical Radiologic Science, Sudan University of Science and Technology, P.O.Box 1908, Khartoum 11111, Sudan
Abstract:IntroductionMedical images are usually affected by biological and physical artifacts or noise, which reduces image quality and hence poses difficulties in visual analysis, interpretation and thus requires higher doses and increased radiographs repetition rate.ObjectivesThis study aims at assessing image quality during CT abdomen and brain examinations using filtering techniques as well as estimating the radiogenic risk associated with CT abdomen and brain examinations.Materials and MethodsThe data were collected from the Radiology Department at Royal Care International (RCI) Hospital, Khartoum, Sudan. The study included 100 abdominal CT images and 100 brain CT images selected from adult patients. Filters applied are namely: Mean filter, Gaussian filter, Median filter and Minimum filter. In this study, image quality after denoising is measured based on the Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and the Structural Similarity Index Metric (SSIM).ResultsThe results show that the images quality parameters become higher after applications of filters. Median filter showed improved image quality as interpreted by the measured parameters: PSNR and SSIM, and it is thus considered as a better filter for removing the noise from all other applied filters.DiscussionThe noise removed by the different filters applied to the CT images resulted in enhancing high quality images thereby effectively revealing the important details of the images without increasing the patients’ risks from higher doses.ConclusionsFiltering and image reconstruction techniques not only reduce the dose and thus the radiation risks, but also enhances high quality imaging which allows better diagnosis.
Keywords:Biological and Physical artifacts  Computed Tomography (CT)  Image Filtering  Radiation risk
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