Fig. 7.

Cells segmentation - Best Gaussian Mixtures Model fit. Initialization of Gaussian mixture model parameters is performed after associating data points to cluster centers using nearest neighbor classification. For the complex object in (a) we have initially C = 6 components (clusters) in the mixture and for the model in (c) C = 17 components. We then apply the Expectation-Maximization (EM) algorithm and use the Minimum Message Length (MML) model selection criterion to identify the number of mixture model components that produces the best model fit. In (b) this results to a reduction of clusters from 6–4, and in (d) from 17–15. Each component in the final model represents a segmented single-cell (see text for details)