Automatic leukocyte classification using cytochemically stained smears.

A leukocyte classification algorithm suitable for automated differential counting has been developed for blood smears stained with a new three-component cytochemical stain which has relatively narrow absorption bands centered at 460, 540 and 640 nm, respectively. The classification procedure is the result of a pattern recognition experiment using a sample of 223 leukocytes distributed evenly over the five normal cell types. The basic data for each cell were three digital microscopic images obtained with narrow band illumination at the above central wavelengths using a TV-digitizer system interfaced to a PDP-15 computer. The classification algorithm involves a sequential decision procedure utilizing five pattern features computed from the intensity histograms of the green and blue digital images. Thus the number of arithmetic operations and the number of computer memory words necessary to perform the classification into one of the five normal white blood cell types are both proportional to n where n is the number of gray levels into which the intensity scale is divided. In this experiment, n equals 256. Comparison of our results with work of others on smears prepared with Romanowski-type stains indicates that such narrow-band, spectrally well separated cytochemical multiple stains can permit the use of algorithms which are approximately ten times faster.