بازسازي تصاوير سي‌تي به روش تكراري مدل پايه

Computed Tomography (CT), consists of two basic parts: sinogram matrix data acquisition and image reconstruction. Many researchers in both fields have tried to use less radiation dose in the imaging process while improving the quality of image. After processing the data acquisition by the CT scanner, the image is obtained using reconstruction algorithms and there are a lot of complex and diverse image reconstruction algorithms. In this research, two methods Filtered Back Projection method (FBP) which is one of the types of analytical algorithms, and the Maximum Likelihood - Expectation Maximization (ML-EM) method which is a Model-Based Iterative algorithms have been investigated. The sinogram matrix data for the image reconstruction process was obtained by MCNPX code and the image reconstruction process has been done by the MATLAB (2022a edition) software, which is an ideal programming language in this field. To eva‎luate these two methods of image reconstruction, various phantoms such as: contrast – detail phantom, resolution phantom and point phantom have been simulated under normal dose and low dose conditions. Also, for more detailed investigation, Signal-to-Nose ratio (SNR) and Contrast-to-Noise ratio (CNR) values and the graph of MTF have been eva‎luated. The results indicate that in low dose imaging conditions, ML-EM method has some advantages than FBP, such as: reducing artifacts and increasing SNR and CNR; But in normal dose imaging conditions, FBP method works as well as ML-EM. We can mention some weaknesses about ML-EM method, such as: longer computing time, change in image texture and smoothed image. Spatial resolution is not always improved in this method. Generally, in normal dose imaging conditions, the FBP method is recommended and in low dose imaging conditions, iterative reconstruction methods are suggested.

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