Faster holographic imaging using recurrent neural networks

Digital holographic imaging is a commonly used microscopy technique in biomedical imaging. It reveals rich optical information of the sample, which could be used, for example, to detect pathological abnormalities in tissue slides. Common image sensors only respond to the intensity of the incoming light. Therefore, reconstructing the complete 3D information of a hologram that is digitally recorded by such sensors has been a challenging task involving optical phase retrieval, which is a time-consuming and computationally intensive step in digital holography.

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