Publication | Open Access
Deep learning enables structured illumination microscopy with low light levels and enhanced speed
35
Citations
16
References
2019
Year
Unknown Venue
EngineeringMicroscopyBiomedical EngineeringStructured Illumination MicroscopySuper-resolution MicroscopySuper-resolution ImagingSingle-image Super-resolutionComputational ImagingLight MicroscopyBiophysicsNovel Imaging MethodDeep Learning EnablesBiophotonicsSuper-resolutionMedical Image ComputingDeep LearningLow Light LevelsIllumination MicroscopyDeep Neural NetworksMicroscope Image ProcessingBiomedical ImagingMedicineCell ImagingSuper-resolution Sim
Abstract Using deep learning to augment structured illumination microscopy (SIM), we obtained a fivefold reduction in the number of raw images required for super-resolution SIM, and generated images under extreme low light conditions (100X fewer photons). We validated the performance of deep neural networks on different cellular structures and achieved multi-color, live-cell super-resolution imaging with greatly reduced photobleaching.
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