Cortical Surface Parcellation Using STAPLE Algorithm
STAPLE大脑皮层表面沟回分割算法

An algorithm for simultaneous truth and performance estimation of various approaches for human cortical surface parcellation was proposed. The probabilistic true segmentation was estimated as a weighted combination of the segmentations resulted from multiple methods. Afterward,an Expectation-Maximization algorithm was used to optimize the weighting depending on the estimated performance level of each method. Furthermore, a spatial homogeneity constraint modeled by the Hidden Markov Random Field theory was incorporated to refine the estimated true segmentation into a spatially homogenous decision. The proposed method was evaluated using both synthetic and real data. Also, it was used to generate reference sulci regions to perform a comparison study of three methods for cortical surface parcel lation. The experimental results demonstrate the validity of the proposed method.