What is it about?
Cells in biological images can look very different - making general techniques to segment them very challenging. Here, we show that in the case of live-cell images (time-lapse movies), the motion of the cells themselves offers a simple, but powerful solution to create a general technique to segment cells using optical flow.
Photo by National Cancer Institute on Unsplash
Why is it important?
Extracting data from biological images is a corner stone of biological research, yet notoriously difficult given how diverse cells can appear. Many techniques rely on specific image characteristics, or vast amounts of labeled training data as strategies to achieve general techniques. Here, we show that a relatively simple use of optical flow offers a robust means to segment single cells. This technique is intuitive, computationally inexpensive, and out performs contemporary techniques.
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This page is a summary of: Robust optical flow algorithm for general single cell segmentation, PLoS ONE, January 2022, PLOS, DOI: 10.1371/journal.pone.0261763.
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