Journal of Pollution

ISSN: 2684-4958

Open Access

Abdou Karim Farota

Gaston Berger University, Saint-Louis · Physique Appliquée PhD

Dynamic live-cell imaging experiments are a powerful tool to interrogate biological systems with single-cell resolution. The key barrier to analyzing data generated by these measurements is image segmentation—identifying which parts of an image belong to which individual cells. Here we show that deep learning is a natural technology to solve this problem for these experiments. We show that deep learning is more accurate, requires less time to curate segmentation results.

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Citations: 64

Journal of Pollution received 64 citations as per Google Scholar report

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