Illumination is often reduced when imaging biological samples. Low-light imaging helps researchers avoid adverse effects, like photobleaching and phototoxicity, that could damage the sample. However, use of low light can affect image quality. The challenge when minimizing illumination is to maintain image quality that is high enough to reflect the underlying biology of the sample and be used for quantitative measurements. Researchers at the University of Adelaide investigated optical fluorescence imaging at low-light levels for quantitative microscopy of live biological samples. Their goal was to determine how ultrasensitive camera technology, including cameras that count individual photons at each pixel, could best be applied to the life sciences. Images taken of a live mouse embryo with and without optimized image capture. Courtesy of the University of Adelaide. Sensitive light detection is necessary to capture biological processes in their natural state. “Damage from illumination is a real concern which can often be overlooked,” professor Kishan Dholakia said. “Using the lowest level of light possible, together with these very sensitive cameras, is important for understanding biology in live and developing cells.” The research team analyzed the performance of scientific cameras, including electron-multiplying charge-coupled devices and scientific CMOS (sCMOS), and developed a tutorial covering the fundamentals of camera operation, including digitization and quantum efficiency. In the tutorial, they discussed sources of camera noise and provided a model of camera noise as a function of incident intensity. They offered methods for assessing camera noise statistics and determining the quality of fluorescence images for practical use. These insights could help researchers evaluate the performance of their own imaging platforms. The team explored deep learning algorithms for the post-processing denoising of fluorescence images. It also examined the effects of user-controllable parameters, such as exposure time and pixel size, on image capture. “A large part of the project involved developing a method to fairly compare the image quality across different cameras,” researcher Zane Peterkovic said. “We even explored how AI can be used to remove noise from the captured images, which is essentially static because the camera struggles to capture enough light.” The researchers illustrated their findings using autofluorescence images of live mammalian embryos captured with a two-photon light sheet fluorescence microscope. “These samples are living, developing specimens that serve as a foundation for studies supporting advancements in clinical IVF,” Dholakia said. The team concluded its tutorial with a discussion about the numerous difficulties and trade-offs associated with fluorescence imaging using scientific cameras. “A lot of natural compounds in cells light up when illuminated, and this can tell us a lot about what we’re looking at, but unfortunately the signal is very weak,” Peterkovic said. Digital camera technology has advanced to the point where fundamental physics concepts like quantum mechanics become relevant, according to Peterkovic. “These steps go beyond just putting the camera in the microscope to take pictures,” he said. “It’s exciting to apply these quantum cameras and use to get the most out of our microscopes.” The study could be a valuable resource for researchers who aim to achieve high-quality imaging under low-light conditions for wide-field microscopy. In the future, the team plans to extend its exploration of low-light imaging systems for live biological samples further into the realm of quantum imaging, where quantum states of light could be used to obtain additional details about the sample. The research was published in APL Photonics (www.doi.org/10.1063/5.0245239).