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UC Berkeley Microscope Captures 25.2 Billion Pixels Per Second at Micron Scale

A new computational microscope uses 48 camera sensors on a credit-card-sized circuit board to image live organisms across five square centimeters at 120 frames per second.

Computational Imaging with Nonlinear Inverse Problems
BIDS Data Science Lecture Series | May 1, 2015 | 1:00-2:30 p.m. | 190 Doe Library, UC Berkeley
Speaker: Laura Waller, Assistant Professor, EECS, Berkeley
Sponsors: Berkeley Institute for Data Science, Data, Society and Inference Seminar

Computat
Computational Imaging with Nonlinear Inverse Prob…      Uc Berkeley Computational Microscope    Berkeley Institute for Data Science (BIDS) / Wikimedia Commons (CC BY 3.0)
By Free News Press Editorial Team
Published August 4, 2026 at 1:14 AM PDT

For decades, engineers building microscopes have faced the same wall: make a microscope faster, and it loses resolution. Widen the field of view, and frame rates drop. A team led by UC Berkeley has now built a microscope that sidesteps all three of those trade-offs at once, capturing video at 25.2 billion pixels per second.

According to Phys.org, the research was published in Nature Photonics. The microscope uses an array of 48 camera sensors, an engineered diffractive optical element, and a computational algorithm to process what it captures. The entire sensor array fits on a single circuit board roughly the size of a credit card.

"This is really a breakthrough in the field of computational microscopy," said Laura Waller, professor of electrical engineering and computer sciences and the study's principal investigator. "With our microscope, we were able to achieve 3-micron resolution across 5 square centimeters at 120 frames per second, which isn't possible with traditional ways. It's the largest space-bandwidth time product of any practical microscope we know of."

The core problem the team had to solve was gaps. When 48 separate sensors sit next to each other on a circuit board, there are physical spaces between them where light does not land. Any light falling in those gaps is lost, meaning portions of the image simply go unrecorded. That missing data makes full image reconstruction difficult.

To fix this, the researchers fabricated a custom phase mask, which is a glass plate placed inside the microscope that bends and redirects light. Instead of light falling into the dead zones between sensors, the mask redirects it onto active sensor surfaces. The team then used compressed sensing techniques in software to reconstruct a complete image from the redirected data.

Waller described the approach as using computational imaging tricks to recover what would otherwise be lost. The phase mask is prefabricated, meaning it does not need to be adjusted each time the microscope is used. The optimization algorithm handles the reconstruction automatically.

The practical consequences of the design are significant for biology research. Many living specimens that scientists want to study move quickly and require wide fields of view. A single organism might be too small to track without high magnification, but also too fast to capture without high frame rates, and too numerous to study meaningfully without imaging a large area at once. Traditional microscopes force researchers to choose which of those requirements to sacrifice.

Waller noted the broader potential of the instrument. "Our approach could be used to image many live organisms simultaneously and to monitor samples over time," she said.

The 25.2 billion pixels per second figure refers to the overall throughput of the system, which researchers describe using a metric called the space-bandwidth time product. This combines resolution, field of view, and frame rate into a single number that reflects how much visual information a microscope can actually capture per second. The team states their instrument achieves the largest such value of any practical microscope currently known.

The sensor array design also offers a path toward scaling. Because the sensors fit on a standard circuit board and the phase mask is fabricated separately, the architecture could in principle be expanded by adding more sensors or redesigning the mask for different wavelengths of light. The current system operates in visible light wavelengths suited to biological imaging.

The research involved collaboration across electrical engineering, computer science, and optical physics. Waller's lab at UC Berkeley has focused for several years on computational approaches to imaging, using software and custom optics together rather than relying solely on conventional lens design. This microscope represents one of the most concrete results of that approach to date, producing a working instrument rather than a theoretical framework.

No timeline for commercial availability has been announced.

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Wide bandgap semiconductors have entered into Nav…      Uc Berkeley Computational Microscope    Salm, Roman Peter. / Wikimedia Commons (Public domain)