Fig. 2.

Segmentations generated from R = 3 synthetic experts with parameters specified as (p₁, q₁) = (0.95, 0.95),(p₂, q₂) = (0.95, 0.90), and (p₃, q₃) = (0.90, 0.90). Only three observations of segmentations by these experts were generated, leading to a small and noisy set of data from which STAPLE was used to estimate the performance parameters and the true segmentation. STAPLE was executed to convergence, initialized with f (T_i = 1) = 0.5 and $(p_j^{(0)},q_j^{(0)})$ = (0.99999, 0.99999), ∀j. Comparisons were made with and without a spatial homogeneity prior modeled with an MRF prior assuming four-nearest-neighbor pairwise interaction cliques and homogeneous interaction strength β = 2.5. The results indicate the estimated T found by STAPLE with the MRF prior exactly matches the specified true segmentation used for the simulations, whereas without this constraint the estimated T is somewhat noisier. In both cases, the estimated performance level parameters were very close to the parameters specified for the random segmentations, (a) Expert 1 segmentation, (b) Expert 2 segmentation, (c) Expert 3 segmentation, (d) STAPLE true segmentation estimate under voxelwise independence assumption, (e) STAPLE true segmentation estimate assuming spatially homogeneous true segmentation.