This study aims to analyze complex prostate MRI images using phase unwrapping and Water-Fat Separation (WFS) methods while considering the effect of noise. The steps include complex image formation, phase unwrapping, testing sensitivity to noise, and separating water and fat components using a dual echo time approach (Dixon method). The unwrapping results show that noise significantly affects the accuracy of phase estimation. At a Noise Parameter of 0.3, the Mean Squared Error (MSE) was 39.62, while increasing the Noise Parameter to 0.7 raised the MSE to 168.89. The separation of water and fat signals was successfully achieved, where the water signal followed the original prostate structure, and the fat signal appeared as a distinct spatial gradient. This study demonstrates that complex MRI image processing of the prostate has strong potential to improve diagnostic accuracy through phase analysis and tissue distribution mapping.
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