‘Robust Statistics’

Constructing Statistically Unbiased Cortical Surface Templates Using Feature Space Covariance

Dec. 19, 2017—Citation: ” Constructing statistically unbiased cortical surface templates using feature-space covariance”. Prasanna Parvathaneni, Ilwoo Lyu, Justin A. Blaber, Yuankai Huo, Allison E. Hainline, Neil D. Woodward, Hakmook Kang, Bennett A. Landman In SPIE Medical Imaging, International Society for Optics and Photonics, 2018 (Accepted). Abstract The choice of surface template plays an important role in cross-sectional subject analyses...

Increased sensitivity to outliers with BPM. Considered a simple one regressor situation, model y = βx + μ is used to fit data points in voxel wise analysis. In SPM, the imaging data (left column) lies along the y axis. (i.e., imaging data is treated as y in the fitted model.) The left column shows two sets of images data, PET blood flow maps (top row) and gray matter (GM) tissue density maps (lower row). The middle column shows the design matrix for each regression. Considered one voxel within mis-registration region, in separated analyses of these datasets with SPM (top and lower rows), a mis-registration induced outlier impacts only on data point in the y-direction. In a joint analysis with BPM, the outlier impacts both the x-axis and y-axis, and can result in dramatically different model fits. In the simulation the true β is a small negative value, but the outliers increase the estimated value of β to make it approximately zero or even a large positive number.

Biological Parametric Mapping WITH Robust AND Non-Parametric Statistics

Jul. 31, 2011—Xue Yang, Lori Beason-Held, Susan M Resnick, Bennett A Landman. “Biological Parametric Mapping with Robust and Non-Parametric Statistics”, NeuroImage 57 (2011) Jul 423–430 PMC3114289† Full text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3114289/ Abstract Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, regions of interest and voxelwise image...