Deep Learning‐Enabled Pixel‐Super‐Resolved Quantitative Phase Microscopy from Single‐Shot Aliased Intensity Measurement (Laser Photonics Rev. 18(1)/2024)
Jie ZhouYanbo JinLinpeng LuShun ZhouHabib UllahJiasong SunQian ChenRan YeJiaji LiChao Zuo
Abstract
Deep Learning-Enabled Pixel-Super-Resolved Quantitative Phase Microscopy A deep learning-based technique for quantitative phase microscopy with pixel super-resolution capability is proposed in article 2300488 by Chao Zuo and co-workers, enabling full-field-of-view, high-resolution and high-speed quantitative phase imaging of unlabeled biological specimens, while requiring only a single frame of low-resolution intensity image as input, demonstrating promising applications in high-throughput cellular analysis.
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