Noise estimation from averaged diffusion weighted images: Can unbiased quantitative decay parameters assist cancer evaluation?

Multiexponential decay parameters are estimated from diffusion‐weighted‐imaging that generally have inherently low signal‐to‐noise ratio and non‐normal noise distributions, especially at high b‐values. Conventional nonlinear regression algorithms assume normally distributed noise, introducing bias into the calculated decay parameters and potentially affecting their ability to classify tumors. This study aims to accurately estimate noise of averaged diffusion‐weighted‐imaging, to correct the noise induced bias, and to assess the effect upon cancer classification.