Microcomputer system for automatic identification of theCryptococcus neoformans and its clinical application

In this study, microcomputer image processing and pattern recognitiontechnology, and the knowledge of morphology and optical characteristics ofCryptococcus neoformans were used for identification ofCryptococcus neoformans. Four groups of mice were lethally infected with standard strain, Wuhan strain, American B-2643 strain and Var. Shanghainesis of theCryptococcus neoformans. The samples collected included mice brain, lung, kidney, liver, small intestine tissue and were observed under a light microscope. More than 600 images of the fungus were input into a microcomputer. A system of computer for automatic identification of theCryptococcus neoformans was developed. The technique involved image preprocessing, image segmenting, coding of line-length on the edge, curve fitting, extracting of image feature, building of image library and feature data bank etc. And then, 768 images of the clinical samples and other fungus samples whose morphological features tend to be confused withCryptococcus neoformans were input into microcomputer and subjected to automatic identification. TheCryptococcus neoformans was accurately identified within 15 min, and the consistence rate with results of routine culture was 98 %.