Document Type : Full Research Paper


Assistant Professor, Biomedical Engineering Department, Hamedan University of Technology, Hamedan, Iran



Molecular magnetic resonance imaging by tracking contrast agents based on magnetic resonance of the nucleus is considered a novel anatomical and functional diagnostic method in various medical applications due to its good spatial resolution and safe technology. In a magnetic resonance scanner, a spectroscopic spectrum known as the Z-spectrum is obtained by applying a predominantly rectangular electromagnetic saturation pulse. At frequencies corresponding to the Larmor frequency, some amplitudes due to water saturation contrast factors are formed, representing saturation transfer’s effect due to chemical exchange (CEST). Chemical shifts, magnetic field heterogeneity and imaging process’s noise, while shifting the Larmore frequencies position, distorts the CEST effect. This noise is mainly modeled by the raisin distribution, which is an extent of Gaussian distribution. In this paper, an efficient method for reducing noise from the Z-spectrum and detecting the CEST effect is presented. Deionization is performed using the analytical model’s output resulting from solving the Bloch-McCannell equations and detecting the CEST effect by calculating the Bayesian likelihood function. The proposed method’s effectiveness for noise cancellation and detection the CEST effect was performed on real Z-spectra which is obtained from magnetic resonance scanners and data obtained from human tissue. The average performance of the proposed method is measured by relative mean square error between the real Z-spectrum and the noise in the signal to noise 10dB and the number of observations 5 was about four percent. The value of the first type of error (p-value) based on parametric data was less than 5% when the noise variance was more than 0.008 and the number of observations was more than 5. In this paper, a criterion for detecting the effect of CEST based on the mediation operator is proposed to evaluate the efficiency of the proposed method in proportion to the noise power and the number of observations.


Main Subjects

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