Cell enumeration and characterization in Microvolume Laser Scanning Cytometry: a multicolor image processing package

Microvolume Laser Scanning Cytometry (MLSC) is an alternative to flow cytometry that has many advantages in clinical environments such as minimal sample preparation, low sample volume, and direct measurement of absolute cell counts. However, MLSC requires an added image-processing step to produce the industry-standard FCS output format. The image processing program needs to handle multiple binary images, representing different detection channels; it needs to determine the background fluorescence level in each channel; the overall noise in each channel such that it can enumerate cell from noise; it needs to ignore extraneous signals such as bubbles, dust particles and other artifacts; and it needs to characterize each recognized cell to report parameters such as weighted flux, size, ellipticity, and ratios and correlations between the signal in other channels at the same location. We have developed an image processing solution, SurroImage(TM) that meets the above criteria and performs well in a clinical research setting.