Automated image analysis for counting unstained cultured neurones

Neuron recognition by parallel Potts segmentation

Identifying neurons and their spatial coordinates in images of the cerebral cortex is a necessary step in the quantitative analysis of spatial organization in the brain. This is especially important in the study of Alzheimer's disease (AD), in which spatial neuronal organization and relationships are highly disrupted because of neuronal loss. To automate neuron recognition by using high-resolution confocal microscope images from human brain tissue, we propose a recognition method based on statistical physics that consists of image preprocessing, parallel image segmentation, and cluster selection on the basis of shape, optical density, and size. We segment a preprocessed digital image into clusters by applying Monte Carlo simulations of a q-state inhomogeneous Potts model. We then select the range of Potts segmentation parameters to yield an ideal recognition of simplified objects in the test image. We apply our parallel segmentation method to control individuals and to AD patients and achieve recognition of 98% (for a control) and 93% (for an AD patient), with at most 3% false clusters.

Semi-automated analysis of NMDA-mediated toxicity in digitised colour images from rat hippocampus

The evaluation of neuronal cell survival after, for example, mechanical, hypoxic or drug-mediated injury requires the analysis of a high number of histological specimens. Since this is a time-consuming occupation, we have developed a semi-automated analysis routine for the determination of the distribution of live and dead cells. After digitalization of the histological preparations, 8-bit colour bitmaps were assessed using a compiled image-analysis programme of the software package Khoros. In the current study a detailed example of the application of this image-processing approach is described for the investigation of the cell survival after intraventricular application of N-methyl-D-aspartate (NMDA). The samples were prepared as fuchsin acid/toluidine blue stained hippocampal thin slices. The calculated areas of the live and dead cells were highly correlated with manual counts of live and dead cells in the 100 samples examined in this study. Twenty-four hours following NMDA-treatment animals (n = 5) were found to have significantly fewer live and more dead hippocampal cells than the saline-treated animals (n = 5), using either automated or manual examination techniques. The automated technique also revealed that NMDA treatment resulted in a reduction in the density of live cell distribution.

Automatic cell culture quantitation with TRAKCELL: application to cell toxicology and differentiation

An automated system, TRAKCELL, was developed for the quantitation of cells in culture. It enabled cell counting, classification according to morphological cell characteristics and measurement of cell proliferation and differentiation. The system was tested on the toxic effect of ascorbic acid on rat brain catecholaminergic neurons in primary culture. In parallel, the effects of nerve growth factor, dexamethasone and forskolin on cell differentiation were studied using rat pheochromocytoma PC12 cells. The results show that the system permits rapid and reproducible measurements of cell density and of the morphological changes observed following various drug treatments.

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

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.