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Optical engineers have historically faced a trade-off between speed, field of view, and resolution in microscope design, where improving one often reduces the others. A UC Berkeley-led team has now demonstrated a computational microscope that overcomes this limitation by integrating 48 camera sensors with a custom diffractive optical element and an optimization algorithm. The system captures videos at 25.2 billion pixels per second, achieving 3-micron resolution across 5 square centimeters at 120 frames per second, a combination previously unattainable with conventional microscopes.

The microscope’s sensor array, arranged on a credit card-sized circuit board, functions as a single large sensor but introduces gaps where light is not captured. To address this, researchers engineered a phase mask to redirect light onto the sensors and used a computational algorithm to reconstruct missing data. This approach eliminates the need for manual calibration, reducing setup time. The team validated the system by imaging static samples with higher resolution than traditional methods and tracking dozens of freely moving C. elegans nematodes at high speed for 15 seconds.

Lead author Kevin C. Zhou, formerly a UC Berkeley postdoctoral researcher and now at the University of Michigan, highlighted the microscope’s ability to track individual worms and perform functional imaging of their rapid pharyngeal pumping, a feeding behavior. The system’s simultaneous high-resolution, wide-field, and high-speed capabilities enable detailed observation of dynamic biological processes that were previously difficult to capture. The researchers emphasized the potential for scaling up imaging systems without the usual labor-intensive calibration processes.

The study, published in Nature Photonics, involved collaboration across multiple institutions, including UCSF, the University of Utah, UC San Diego, and Duke University. Funding was provided by the Office of Naval Research, the Air Force Office of Scientific Research, the National Institutes of Health, and the Japan Society for Promotion of Science. Laura Waller, a Chan Zuckerberg Biohub SF investigator, led the project, which she described as a step toward advancing large-scale video microscopy through joint hardware and software design.