Method of Tracking and Analysis of Fluorescent-Labeled Cells Using
  Automatic Thresholding and Labeling
Mizuki Fukasawa Tomokazu Fukuda Takuya Akashi
High-throughput screening using cell images is an efficient method for
screening new candidates for pharmaceutical drugs. To complete the screening
process, it is essential to have an efficient process for analyzing cell
images. This paper presents a new method for efficiently tracking cells and
quantitatively detecting the signal ratio between cytoplasm and nuclei.
Existing methods include those that use image processing techniques and those
that utilize artificial intelligence (AI). However, these methods do not
consider the correspondence of cells between images, or require a significant
amount of new learning data to train AI. Therefore, our method uses automatic
thresholding and labeling algorithms to compare the position of each cell
between images, and continuously measure and analyze the signal ratio of cells.
This paper describes the algorithm of our method. Using the method, we
experimented to investigate the effect of the number of opening and closing
operations during the binarization process on the tracking of the cells.
Through the experiment, we determined the appropriate number of opening and
closing processes.