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IVF advancement: New camera techniques transform biological imaging

ADELAIDE, Australia — In a breakthrough at the intersection of quantum physics and biology, researchers at the University of Adelaide have figured out a way to observe the earliest stages of life. Using cameras designed for quantum measurements, these scientists have captured unprecedented images of developing embryos while minimizing the damage typically caused by conventional imaging techniques.

Their research, published in the journal APL Photonics, serves as a roadmap for scientists navigating the world of low-light imaging. The central idea is both simple and powerful: by optimizing camera settings and employing quantum-inspired detection technology rather than increasing illumination intensity, researchers can achieve better image quality while minimizing damage to living specimens.

“Damage from illumination is a real concern which can often be overlooked. Using the lowest level of light possible, together with these very sensitive cameras is important for understanding biology in live and developing cells,” says Professor Kishan Dholakia, director of the University’s Centre of Light for Life and one of the study’s authors, in a statement.

Consider the delicate mouse embryo, a living structure so sensitive to light that excessive illumination can disrupt its development or even kill it. Yet scientists need clear images to study its intricate cellular processes. This is the fundamental challenge of biological imaging—getting enough signal without destroying the very thing you’re trying to observe.

“These samples are living, developing specimens that serve as a foundation for studies supporting advancements in clinical IVF,” notes Professor Dholakia.

Beyond the camera: Why the right settings are crucial

The research shows that picking the right camera is just the first step. What really matters is knowing how to optimize settings for specific imaging challenges. By testing three different camera types—the ORCA-Flash V3, ORCA-Quest, and iXON Life 888—the team demonstrated how tweaking various settings dramatically improved image quality without increasing light intensity.

One key setting is “pixel binning,” which combines multiple pixels into one larger virtual pixel. This allows the camera to collect more light in each measurement, though at the cost of some image detail. Another important setting is exposure time—how long the camera collects light before taking a reading.

In one striking example, when imaging a mouse embryo, switching from standard settings to optimized settings (2×2 pixel binning, longer exposure time, and specialized camera mode) boosted the signal-to-noise ratio from 1.78 to 5.6—without any additional illumination. Signal-to-noise ratio (SNR) is a measure of how clear and reliable an image is—higher numbers mean cleaner images where the biological structures stand out more clearly from background noise.

The science behind these improvements relates to light’s fundamental nature. At extremely low intensities, light behaves more like individual particles (photons) than waves. Modern quantum-inspired cameras can detect these individual packets of light energy at each pixel, allowing for unprecedented sensitivity.

“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,” said lead author and PhD student Zane Peterkovic.

The differences between cameras

Different camera designs handle this challenge in different ways. sCMOS (scientific Complementary Metal Oxide Semiconductor) cameras like the ORCA-Flash and ORCA-Quest offer excellent resolution with relatively low noise, working similarly to advanced versions of digital camera sensors in smartphones but with much higher precision. Meanwhile, EMCCD (Electron-Multiplying Charge-Coupled Device) cameras like the iXON Life excel at detecting extremely faint signals by amplifying electrons before they’re read out—similar to turning up the volume on a weak audio signal before processing it.

Each camera type has its trade-offs. EMCCDs are incredibly sensitive but suffer from “excess noise factor”—the amplification process itself introduces additional uncertainty, like how turning up the volume also amplifies static in an audio recording. sCMOS cameras have lower sensitivity but don’t have this excess noise problem.

The paper avoids getting stuck in theory, focusing instead on practical examples. When imaging embryos that naturally emit light without added dyes, the researchers show how to balance pixel size, exposure time, and camera mode for best results.

“A large part of the project involved developing a method to fairly compare the image quality across different cameras,” explains Peterkovic.

Perfecting the image

One key finding challenges a common practice. Many scientists instinctively crank up magnification to capture more detail, but the research shows there’s a physical limit to how much detail can be resolved due to light diffraction. Higher magnification beyond this point just spreads the same information across more pixels, reducing signal intensity without gaining additional information. This insight helps researchers select appropriate magnification that maximizes signal without unnecessary light exposure.

The team also tested machine learning algorithms to enhance low-light images. Three different denoising algorithms—Noise2Fast, Neighbor2Neighbor, and Accurate Correction of sCMOS Noise (ACsN)—showed promise but came with warnings about potential artifacts or “hallucinations” if not used carefully. Denoising algorithms work like digital filters that try to remove random speckles and static from images while preserving the true biological structures.

“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,” says Peterkovic. “These steps go beyond just putting the camera in the microscope to take pictures.”

The excitement of quantum camera tech

For scientists working with living specimens, the benefits are clear. These optimization strategies reduce phototoxicity and photobleaching—two major problems in live-cell imaging. Phototoxicity refers to how light can poison or damage living cells, similar to severe sunburn at a cellular level. Photobleaching is when fluorescent molecules fade under light exposure, like how fabrics fade in strong sunlight. Both problems are reduced when less light is needed for imaging.

“It’s exciting to apply these quantum cameras and use it to get the most out of our microscopes,” Peterkovic adds. “Digital camera technology has advanced to the point where fundamental physics concepts like quantum mechanics become important and relevant.”

Surprisingly, the tutorial reveals that even relatively inexpensive cameras can achieve impressive results when properly optimized, making high-quality imaging more accessible to labs with limited resources.

“Modern imaging technology is very exciting with what it enables us to see,” remarked Professor Dholakia.

The authors argue that understanding camera physics and optimization techniques isn’t merely a technical exercise—it’s essential for responsible research that minimizes harm to living specimens while maximizing scientific insight. As microscopy pushes the boundaries of what we can see in the biological world, these principles will only grow in importance.

Future work will extend into quantum imaging, where quantum states of light may reveal even more information about samples. For low-light microscopy, the message is clear: quantum-inspired cameras that detect the faintest signals can revolutionize how we study the beginning of life.