Abstract
Edge detection in images is a key problem in quantitative cell biology, nanophotonics and other areas, but the edge-detection algorithms that have been developed suffer from serious limitations in precision. This year, we presented a computational method for super-resolution edge detection in single standard images that opens the possibility of detecting shapes of objects with features much smaller than the microscope’s point spread function.
© 2020 Optical Society of America
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