Assessing the anatomical correlation of atherosclerosis with biomechanical localizing factors is hindered by spatial autocorrelation (SA), wherein neighboring arterial regions tend to have similar properties rather than being independent, and by the use of aggregated data, which artificially inflates correlation coefficients. Resampling data at lower resolution or reducing degrees-of-freedom in significance tests negated effects of SA but only in artificial situations where it occurred at a single length scale. Using Fourier or wavelet transforms to generate autocorrelation-preserving surrogate datasets, and thus to compute the null distribution, avoided this problem. Bootstrap methods additionally circumvented the errors caused by aggregating data. The bootstrap technique showed that wall shear stress (WSS) was significantly correlated with atherosclerotic lesion frequency and endothelial nuclear elongation, but not with the permeability of the arterial wall to albumin, in immature rabbits.
Generalized Organ Segmentation by Imitating One-Shot Reasoning Using Anatomical Correlation
