A Robust and Automated Method for Estimating the Expected Signal Standard Deviation in DWI Datasets

Keywords

absolute acceptable acquiring acquisitions added additional address advantage although applied arises artifacts automated background basis better book brain catholic certain channel classical clinical collection company completely compute computed computer consuming correctly corrupted corruption created dataset datasets defined denote derived described deviation diffusion distributed distribution done effectiveness electrical eliminating engineering error estimating estimation estimator even examples expected extract extracting filtering fitting formula free fully ghost hardware health human identical important improves institutes intensity location measured measuring median medical meeting minus modalities modern multiplied multiplying national needed noise object original outliers outperformed parallel percentage performance physics practical presence problem processing propose proposed quadrature quantitative ranging rarely reconstruction reduced reflects regardless registration regression remove removes replicated replicates reproducibility required residual residuals respectively robust sample scalar scheme severity similarly simulate simulated simulations situation slightly solve specifies squares step still synthetic system tail takes tasks tensor thermal true types underestimated underestimation user validate volume volumes walker