Detecting mitoses in time-lapse images of embryonic epithelia using intensity analysis.

Although the frequency and orientation of mitoses can significantly affect the mechanics of early embryo development, these data have not been available due to a shortage of suitable automated techniques. Fluorescence imaging, though popular, requires biochemical intervention and is not always possible or desirable. Here, a new technique that takes advantage of a localized intensity change that occurs in bright field images is used to identify mitoses. The algorithm involves mapping a deformable, sub-cellular triangular mesh from one time-lapse image to the next so that corresponding regions can be identified. Triangles in the mesh that undergo darkening of a sufficient degree over a period consistent with mitosis are flagged. Mitoses are assumed to occur along the short axis of elliptical areas fit to suitably sized clusters of flagged triangles. The algorithm is less complex than previous approaches and it has strong discrimination characteristics. When applied to 15 image sets from neurulation-stage axolotl (Ambystoma mexicanum) embryos, it was able to correctly detect 86% of the manually identified mitoses, had less than 5% false positives and produced average angular errors of only 15 degrees . The new algorithm is simpler to implement than those previously available, is substantially more accurate, and provides data that is important for understanding the mechanics of morphogenetic movements.