A team of engineers led by computer scientists at the University of California, San Diego, has developed a new approach that marries computer vision and hardware optimization to sort cells up to 38 times faster than is currently possible. The approach could be used for clinical diagnostics, stem cell characterization and other applications. The 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 4 meters per second. The technique sorts cells into different categories, for example benign or malignant cells, based on their shape and structure. If these features can be calculated fast enough, the cells can be sorted in real-time.
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