Duke University scientists have engineered a holographic system that can image and analyze tens of thousands of cells per minute to identify disease indicators.
Sample cells can be washed off the collector into a biocompatible solution and deposited into a microfluidic chip; the sample flows into channels under a line camera.
The camera reads the illuminated cells' topography and calculates their features, which when combined with data points and deep learning, can serve as disease-spotting markers.
The system differentiated between healthy and cancerous or carcinogen-exposed pre-cancerous cells with 98% to 99% accuracy.
Duke's Cindy Chen said, "The idea is that, by having this wealth of quantitative data, you can separate the cells better than if you were using one single metric."
From Duke Pratt School of Engineering
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