Automated Measurement of <em>Cryptococcal</em> Species Polysaccharide Capsule and Cell Body

Abstract

The purpose of this technique is to provide a consistent, accurate, and manageable process for large numbers of polysaccharide capsule measurements. First, a threshold image is generated based on intensity values uniquely calculated for each image. Then, circles are detected based on contrast between the object and background using the well-established Circle Hough Transformation (CHT) algorithm. Finally, the detected cell capsules and bodies are matched according to center coordinates and radius size, and data is exported to the user in a manageable spreadsheet. The advantages of this technique are simple but significant. First, because these calculations are performed by an algorithm rather than a human both accuracy and reliability are increased. There is no decline in accuracy or reliability regardless of how many samples are analyzed. Second, this approach establishes a potential standard operating procedure for the Cryptococcus field instead of the current situation where capsule measurement varies by lab. Third, given that manual capsule measurements are slow and monotonous, automation allows rapid measurements on large numbers of yeast cells that in turn facilitates high throughput data analysis and increasingly powerful statistics. The major limitations of this technique come from how the algorithm functions. First, the algorithm will only generate circles. While Cryptococcus cells and their capsules take on a circular morphology, it would be difficult to apply this technique to non-circular object detection. Second, due to how circles are detected the CHT algorithm can detect enormous pseudo-circles based on the outer edges of several clustered circles. However, any misrepresented cell bodies caught within the pseudo-circle can be easily detected and removed from the resulting data sets. This technique is meant for measuring the circular polysaccharide capsules of Cryptococcus species based on India Ink bright field microscopy; though it could be applied to other contrast based circular object measurements.