Jun. 19, 2019
Applications

AI for Reliable Cell Quantification in Ultra-Low Light

  • Fig. 1: DAPI-labeled HeLa cells imaged at optimal light intensity (a) and at 2% (b), 0.2% (c) and 0.05% (d) of optimal intensity (contrast optimized for visualization only).Fig. 1: DAPI-labeled HeLa cells imaged at optimal light intensity (a) and at 2% (b), 0.2% (c) and 0.05% (d) of optimal intensity (contrast optimized for visualization only).
  • Fig. 1: DAPI-labeled HeLa cells imaged at optimal light intensity (a) and at 2% (b), 0.2% (c) and 0.05% (d) of optimal intensity (contrast optimized for visualization only).
  • Fig. 2: Cell cycle analysis at 100% (left) and 0.2% light intensity (right).

Quantitative live cell fluorescence microscopy usually requires high light intensity to achieve sufficient contrast – potentially affecting cell behavior. Olympus’ AI-based high content screening software can reliably analyze cell nuclei in ultra-low light conditions and generate precise data while avoiding phototoxicity. Artificial intelligence (AI) has recently emerged as a valuable tool for high-throughput analysis of microscopy images. As the capabilities of AI-based systems have improved, it has become possible to detect features and contours that are hard to see with the human eye. One application where these capabilities are particularly valuable is the analysis of images captured in ultra-low light.

Download the complete application note here.

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Amsinckstraße 63
20097 Hamburg
Germany
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