Detection of Differentiated vs. Undifferentiated Colonies of iPS Cells Using Random Forests Modeled with the Multivariate Polya Distribution

Abstract

In this paper we propose a novel method for automatic detection of undifferentiated vs. differentiated colonies of iPS cells, which is able to achieve excellent accuracy of detection using only a few training images. Local patches in the images are represented through the responses of texture-layout filters over texton maps and learned using Random Forests. Additionally, we propose a novel method for probabilistic modeling of the information available at the leaves of the individual trees in the forest, based on the multivariate Polya distribution.