University of California, San Diego (UCSD) researchers say they have developed an approach that combines computer vision and hardware optimization to sort cells up to 38 times faster than is currently possible. Their approach improves on a technique known as imaging flow cytometry, which uses a camera mounted on a microscope to capture the morphological features of hundreds to thousands of cells per second while the cells are suspended in a solution moving at approximately four meters to second.
UCSD professor Ryan Kastner says their technique has the potential "to lead to a number of clinical breakthroughs, and we are working closely with UCLA and their industrial partners to commercialize our technology."
Although researchers had previously discovered that the physical properties of cells could provide useful information about cell health, the new approach brings imaging flow cytometry closer to being used in a clinical setting.
The microscope-mounted camera used in imaging flow cytometry operates at 140,000 frames per second. However, current algorithms can take up to 10 seconds to analyze a single frame, making the technique impractical.
The new approach speeds processing speeds up to 11.94 milliseconds and 151.7 milliseconds depending on the type of hardware used. The researchers aim to analyze the cell properties in real time, and use that information to sort the cells.
From UCSD News (CA)
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