The third major release of our free open-source software CellProfiler is designed to help biologists working with images, whether a few or thousands. Thus, many biologists find they need software to analyze images easily and accurately.
Looking at the resulting images by eye would be extremely tedious, not to mention subjective. The “big-data revolution” has struck biology: it is now common for robots to prepare cell samples and take thousands of microscopy images. FluoroCellTrack demonstrates an average of a ~92-99% similarity with manual analysis and exhibits a significant reduction in analysis time of 30 min to analyze an entire cohort compared to 20 h required for manual quantification. Individually detected droplet and contour center maps are overlaid to obtain encapsulation information for further analyses. These feature detection steps are strengthened by segmentation and radius/ area thresholding for precise detection and removal of false positives. Two parallel steps are performed where droplets are detected using a mathematical Circular Hough Transform (CHT) while single cells (or other contours) are detected by a series of steps defining respective color boundaries involving edge detection, dilation, and erosion. The algorithm imports all images collected using bright field and fluorescence microscopy and analyzes them to extract useful information. To address these issues, an all-in-one Python algorithm called FluoroCellTrack was developed and its wide-range utility was tested on three different applications including quantification of cellular response to drugs, droplet tracking, and intracellular fluorescence. Existing quantification tools have limitations including interdependent hardware platforms or challenges analyzing a wide range of high-throughput droplet microfluidic data using a single algorithm. While there have been significant advances in the field of experimental droplet microfluidics, the development of complementary software tools has lagged. High-throughput droplet microfluidic devices with fluorescence detection systems provide several advantages over conventional end-point cytometric techniques due to their ability to isolate single cells and investigate complex intracellular dynamics.
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