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Turning a Cell Phone Into a Microscope
stupendou writes with this excerpt from the New York Times: "Microscopes are invaluable tools to identify blood and other cells when screening for diseases like anemia, tuberculosis and malaria. But they are also bulky and expensive. Now an engineer, using software that he developed and about $10 worth of off-the-shelf hardware, has adapted cellphones to substitute for microscopes." But not based on optical magnification: the article explains that Aydogan Ozcan, a UCLA assistant professor of electrical engineering, has combined the wireless transmission abilities and imaging sensors now typical in wireless phones to make the phones capable of detecting cell abnormalities and more by capturing wave interference patterns from body fluids — like blood — and sending them on for analysis.
Update 20091108 15:03 GMT by timothy: Dave Bullock mentions this gallery he shot last year for Wired showing how a phone is hacked to add microscope abilities. "The new version looks a bit more polished, to say the least," he writes.
Update 20091108 15:03 GMT by timothy: Dave Bullock mentions this gallery he shot last year for Wired showing how a phone is hacked to add microscope abilities. "The new version looks a bit more polished, to say the least," he writes.
A high-throughput on-chip imaging platform that can rapidly monitor and characterize various cell types within a heterogeneous solution over a depth-of-field of ~4mm and a field-of-view of ~10 cm^2 is introduced. This powerful system can rapidly image/monitor multiple layers of cells, within a volume of ~4 mL all in parallel without the need for any lenses, microscope-objectives or any mechanical scanning.
In this high-throughput lensless imaging scheme, the classical diffraction pattern (i.e., the shadow) of each micro-particle within the entire sample volume is detected in less than a second using an opto-electronic sensor chip. The acquired shadow image is then digitally processed using a custom developed ‘‘decision algorithm’’ to enable both the identification of the particle location in 3D and the characterization of each micro-particle type within the sample volume.
Through experimental results, we show that different cell types (e.g., red blood cells, fibroblasts, etc.) or other micro-particles all exhibit uniquely different shadow patterns and therefore can be rapidly identified without any ambiguity using the developed decision algorithm, enabling high-throughput characterization of a heterogeneous solution.
http://www3.interscience.wiley.com/journal/121401991/abstract
http://www3.interscience.wiley.com/cgi-bin/fulltext/121401991/PDFSTART
This topic was also covered a few months ago -- with better results, but using actual lenses instead of just the bare CCD sensor:
http://science.slashdot.org/story/09/07/24/1440227/Use-Your-Cell-Phone-To-Diagnose-Blood-Diseases