A combined Markov and noise clustering modeling method for cell phase classification

Abstract

This paper proposes a classification method of cell nuclei in different mitotic phases using a combined Markov and noise clustering modeling technique. The method was tested with the data set containing 379519 cells in 892 cell sequences for 5 phases extracted from real image sequences recorded at every fifteen minutes with a time-lapse fluorescence microscopy. Experimental results showed that the proposed method performed better than the k-means modeling method.