‘SIMEX’

Resilience features capture the stability of an inference method to data decimation. An rs-fMRI dataset (1) is temporally decimated into subsets; each inference method (2) is applied independently to each subset; voxel-wise statistics (3) are estimated; and the parameter maps (4) capture spatial dependencies.

Quantitative Evaluation of Statistical Inference in Resting State Functional MRI

Sep. 30, 2012—Xue Yang and Bennett A. Landman. “Quantitative Evaluation of Statistical Inference in Resting State Functional MRI”, In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Nice, France, September 2012 (32% acceptance rate) Full text: https://www.ncbi.nlm.nih.gov/pubmed/23286055 Abstract Modern statistical inference techniques may be able to improve the sensitivity and specificity of resting state functional...

Flow chart of steps to create SIMEX Estimated Bias and True Bias maps. Variables refer to terms defined explicitly by equations in the Theory section.

Assessment of bias for MRI diffusion tensor imaging using SIMEX

Sep. 30, 2011—Carolyn B. Lauzon, Andrew Asman, Ciprian Crainiceanu, Brian Caffo, Bennett A. Landman. “Assessment of Bias for MRI Diffusion Tensor Imaging Using SIMEX”, In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Toronto, Canada, September 2011 (30% acceptance rate) NIHMS ID 301343 Full text: https://www.ncbi.nlm.nih.gov/pubmed/21995019 Abstract Diffusion Tensor Imaging (DTI) is a Magnetic Resonance...