Monte Carlo-based noise compensation in coil intensity corrected endorectal MRI.

摘要: Prostate cancer is one of the most common forms found in males making early diagnosis important. Magnetic resonance imaging (MRI) has been useful visualizing and localizing tumor candidates with use endorectal coils (ERC), signal-to-noise ratio (SNR) can be improved. The introduce intensity inhomogeneities surface coil correction built into MRI scanners used to reduce these inhomogeneities. However, typically performed at scanner level leads noise amplification variations. In this study, we a new Monte Carlo-based compensation approach for corrected which allows effective preservation details within prostate. accounts ERC SNR profile via spatially-adaptive model correcting non-stationary Such method particularly improving image quality data when original raw not available. contrast-to-noise (CNR) analysis patient experiments demonstrate an average improvement 11.7 11.2 dB respectively over uncorrected MRI, provides strong performance compared existing approaches. Experimental results using both phantom showed that ACER provided terms SNR, CNR, edge preservation, subjective scoring number A was developed purpose level. We illustrate promising achieved proposed approach, important processing