The analysis of cell function comprises an examination of gene expression, protein synthesis, and metabolic activity. In order to measure these parameters in single cells a means for signal transduction and amplification is required. Fluorescent molecules have been demonstrated to provide a powerful tool for this detection need when performing living cell analysis. The development of an image analysis tool is the first step in automating multi-parameter cell function analysis where the objective is to ascertain cell membrane integrity and by extension, to obtain an estimate of cell health. A live/dead fluorescent stain was used to make this distinction. Two image analysis algorithms were implemented from the literature and one new method was developed. Three methods were tried: threshold segmentation, matched filtering, and an original method named morphological subtraction. The threshold technique produced the greatest overall accuracy in reducing spurious counts, closely followed by the morphological subtraction and then the matched filter. However, the original morphological subtraction method may be more appropriate in single cell studies because it overestimates live cells, aiding in the identification of unsuitable data.