Real-time LOC-based morphological cell analysis system using high-speed vision

In this paper, a high-speed vision-based morphological analysis system for fast-flowing cells in a microchannel implementing a multi-object feature extraction algorithm on a high-speed vision platform is proposed. Real-time video processing is performed in hardware logic by extracting the moment features and bounding boxes of multiple cells in 512×256-pixel images at 2000 fps. The extracted cell regions are pushed into a first-in-first-out (FIFO) buffer for real-time image-based morphological analysis after being shrunk proportionally to a certain size. By extracting the bounding boxes of the cell regions using hardware logic and shrinking the cell region to a certain size to reduce processing time, our high-speed vision system can perform fast morphological analysis of cells at 2 ms/cell in fast microchannel flows. The results of real-time experiments conducted to analyze the size, eccentricity, and transparency of fertilized sea urchin eggs fast flowing in microchannels verify the efficacy of our vision-based cell analysis system.