Supplementary material for Development of a motion-based cell-counting system for Trypanosoma parasite using a pattern recognition approach

Yuko Takagi, Hirokazu Nosato, , Koji Furukawa & Hidenori Sakanashi
Automated cell counters that utilize still images of sample cells are widely used. However, they are not well suited to counting slender, aggregate-prone microorganisms such as Trypanosoma cruzi. Here, we developed a motion-based cell-counting system, using an image-recognition method based on a cubic higher-order local auto-correlation feature. The software successfully estimated the cell density of dispersed, aggregated, as well as fluorescent parasites by motion pattern recognition. Loss of parasites activeness due to drug treatment could...
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