High-content imaging has become a cornerstone of life science research, providing valuable insights into cellular function and drug responses. However, as with any advanced technology, misconceptions and myths can emerge. In this article, we’ll debunk some of the most common myths surrounding high-content imaging, shedding light on its true strengths and limitations.
- Learn how image quality depends more on optical architecture than just light source type.
- Learn why increasing laser lines isn't always necessary for higher multiplexing and how to achieve better results with fewer, optimally selected wavelengths.
- Discover why data quality, not quantity, should drive imaging decisions, and how to optimize magnification, field of view, and z-stacks.
- Understand the potential and limitations of AI in image analysis, including the importance of transparency and data bias awareness.