Dynamic Time Warping for Automated Cell Cycle Labelling
نویسندگان
چکیده
With the widespread use of time-lapse data to understand cellular function, there is a need for tools which facilitate high-throughput analysis of data. We present a system for automated segmentation and cell cycle phase labelling based on aligning temporal signals of simple features directly to a reference signal using Dynamic Time Warping (DTW). This is shown to result in a very accurate temporal labelling, significantly outperforming an approach based on independent frame classification. The method is evaluated on two datasets, acquired under different imaging conditions, and is found to perform well on both. We also describe a Hidden Markov Model implementation of the DTW which has comparable results.
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