Toward a Thinking Microscope: Deep Learning in Optical Microscopy and Image Reconstruction
arXiv:1805.08970 · doi:10.1364/OPN.29.7.000034
Abstract
We discuss recently emerging applications of the state-of-art deep learning methods on optical microscopy and microscopic image reconstruction, which enable new transformations among different modes and modalities of microscopic imaging, driven entirely by image data. We believe that deep learning will fundamentally change both the hardware and image reconstruction methods used in optical microscopy in a holistic manner.
References in corpus (5)
- Phase recovery and holographic image reconstruction using deep learning in neural networks
- Deep Learning Microscopy
- Deep-STORM: super-resolution single-molecule microscopy by deep learning
- Extended depth-of-field in holographic image reconstruction using deep learning based auto-focusing and phase-recovery
- Lensless computational imaging through deep learning