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Deep learning-driven computational imaging for light field microscopy
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DOI：10.1142/S1793545826300089.png)
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Abstract
En 中文
Light field microscopy (LFM), with its snapshot-based three-dimensional imaging capability, has become a vital tool for observing dynamic living specimens. To overcome limitations in resolution and reconstruction speed inherent in traditional algorithms, the application of deep learning to light field microscopic imaging has emerged as a key development direction. This review will introduce the basic theory and classical algorithms of LFM, survey the application of deep learning-based methods in computational image enhancement and analysis, and discuss the associated challenges and future research directions.
Keywords:
Light field
deep learning
reconstruction algorithm
computational imaging
Journal
J
IF:
2.2
Papers:
44
Citations:
1.1K