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Title: OPTIMIZATION ANALYSIS OF CT SYSTEM IMAGING
Authors: Yingxia Liu , Hanjiang Dong, Lubin Wu, Feizheng Xu, Rui Deng
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Yingxia Liu , Hanjiang Dong, Lubin Wu, Feizheng Xu, Rui Deng Mathematical modeling base, zhuhai campus, jinan university, China
MLA 8 Liu, Yingxia, et al. "OPTIMIZATION ANALYSIS OF CT SYSTEM IMAGING." Int. j. of Social Science and Economic Research, vol. 3, no. 11, Nov. 2018, pp. 6245-6259, ijsser.org/more2018.php?id=435. Accessed Nov. 2018. APA Liu, Y., Dong, H., Wu, L., Xu, F., & Deng, R. (2018, November). OPTIMIZATION ANALYSIS OF CT SYSTEM IMAGING. Int. j. of Social Science and Economic Research, 3(11), 6245-6259. Retrieved from ijsser.org/more2018.php?id=435 Chicago Liu, Yingxia, Hanjiang Dong, Lubin Wu, Feizheng Xu, and Rui Deng. "OPTIMIZATION ANALYSIS OF CT SYSTEM IMAGING." Int. j. of Social Science and Economic Research 3, no. 11 (November 2018), 6245-6259. Accessed November, 2018. ijsser.org/more2018.php?id=435.
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Abstract: Aiming at the problem of how to reconstruct an image based on the absorbed data from the unknown medium using the CT system with known calibration parameters, this paper proposed the Optimized filtered back-projection model of Image Denoising. This model first uses the Ramp-Lak filtered back-projection algorithm to reconstruct the image of the unknown medium to obtain the position and geometry of the medium. Then, considering the limitations of the single filtered back-projection algorithm, Shepp-Logan filtered back-projection algorithm and Lewitt filtered back-projection algorithm was used separately to reconstruct the CT image. Then the gray-scale variance function is used to calculate the sharpness of the above three groups of images. The image used the Ramp-Lak filtered back-projection algorithm got the highest score, indicating that the resolution is the best. Then, because the noise signal generated during the back-projection of the image will affect the sharpness of the image, the Wiener algorithm is used to denoise the image with the highest score above, so that the noise of the image is greatly reduced. A clearer image result is obtained, which more accurately determines the position and geometry of the unknown medium, and provides a reference value for imaging of the CT system.

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