AUTOMATED IMAGE ANALYZING SYSTEM FOR THE QUANTITATIVE STUDY OF LIVINGCELLS IN CULTURE

A fully automated image analyzing system was developed for the quantit ative study of cells in culture. It was able to count cells, to classi fy cells according to their morphological characteristics and to follo w cell culture development. A specific procedure was designed to proce ss Hoffman modulation contrast images. It detects local gray level dif ferences 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 noninvas ive and nondestructive way with this system. An improved automatic foc using 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 hams ter ovary (CHO-NTR) cell cultures treated with a newly developed neuro tensin agonist JMV449. Chinese hamster ovary cell division was found t o be retarded 20 hours after the JMV449 treatment, while the morpholog y of CHO-NTR cells has already undergone significant changes 12 hours after the treatment. This image analyzing system provides the possibil ity to follow cell culture development (e.g., cell density evolution, cell morphological changes) under various experimental conditions. (C) 1994 Wiley-Liss, Inc.