A Stochastic Framework for Improving the Accuracy of PIESNO

Cheng Guan Koay¹, Evren Ozarslan¹, Carlo Pierpaoli¹, Peter J. Basser¹

Probabilistic Identification and Estimation of Noise (PIESNO) is a recent technique capable of identifying noise-only pixels in magnitude-reconstructed MR images. The identification criterion and the estimation method used in PIESNO were chosen and constructed for expediency in terms of computational efficiency and theoretical simplicity rather than for accuracy. Although a strictly theoretical approach to determine the exact level of bias in the estimate of noise level through PIESNO seems to be intractable, it is still worthwhile to use stochastic framework for determining the level of bias. Here, we present one such framework for improving the accuracy of PIESNO.