Automated image analyzing system for the quantitative study of living cells in culture

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Abstract
A fully automated image analyzing system was developed for the quantitative study of cells in culture. It was able to count cells, to classify cells according to their morphological characteristics and to follow cell culture development. A specific procedure was designed to process Hoffman modulation contrast images. It detects local gray level differences while using conditional dilation techniques. We were able to successfully detect aggregated unstained cells, presently a technical limit in image segmentation. Living cells can be studied in a noninvasive and nondestructive way with this system. An improved automatic focusing algorithm was developed which ensured an accurate prediction of the optimal focus position. A strictly defined sampling procedure was applied to estimate unbiasedly cell density and obtain precisely cell contours. The evaluation of the system was carried out on Chinese hamster ovary (CHO-NTR) cell cultures treated with a newly developed neurotensin agonist JMV449. Chinese hamster ovary cell division was found to be retarded 20 hours after the JMV449 treatment, while the morphology of CHO-NTR cells has already undergone significant changes 12 hours after the treatment. This image analyzing system provides the possibility to follow cell culture development (e.g., cell density evolution, cell morphological changes) under various experimental conditions.