mlsanityData to 7 Oct 2026

Diffractive all-optical computing for quantitative phase imaging

arXiv 2201.08964 ↗First posted 22 Jan 2022physics.optics cs.CV cs.NEcited by 22

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Abstract (arXiv)

Quantitative phase imaging (QPI) is a label-free computational imaging technique that provides optical path length information of specimens. In modern implementations, the quantitative phase image of an object is reconstructed digitally through numerical methods running in a computer, often using iterative algorithms. Here, we demonstrate a diffractive QPI network that can synthesize the quantitative phase image of an object by converting the input phase information of a scene into intensity variations at the output plane. A diffractive QPI network is a specialized all-optical processor designed to perform a quantitative phase-to-intensity transformation through passive diffractive surfaces that are spatially engineered using deep learning and image data. Forming a compact, all-optical network that axially extends only ~200-300 times the illumination wavelength, this framework can replace traditional QPI systems and related digital computational burden with a set of passive transmissive layers. All-optical diffractive QPI networks can potentially enable power-efficient, high frame-rate and compact phase imaging systems that might be useful for various applications, including, e.g., on-chip microscopy and sensing.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). Builds on 11 of its 65 references that are in the map. First posted on arXiv 22 Jan 2022.

Builds on

11 of 65 references.

References · 11

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2017Deep Learning for Medical Image Analysiscited by 399
  3. 2017A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasetscited by 374
  4. 2018All-Optical Machine Learning Using Diffractive Deep Neural Networkscited by 175
  5. 2017Phase recovery and holographic image reconstruction using deep learning in neural networkscited by 54
  6. 2020Misalignment Resilient Diffractive Optical Networkscited by 33
  7. 2018Analysis of Diffractive Optical Neural Networks and Their Integration with Electronic Neural Networkscited by 30
  8. 2019Design of Task-Specific Optical Systems Using Broadband Diffractive Neural Networkscited by 27
  9. 2021All-Optical Synthesis of an Arbitrary Linear Transformation Using Diffractive Surfacescited by 24
  10. 2018Deep learning-based super-resolution in coherent imaging systemscited by 7
  11. 2018Solving Fourier ptychographic imaging problems via neural network modeling and TensorFlowcited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 8; 2023: 6; 2024: 5; 2025: 1; 2026: 2.

22 papers.

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  1. 2023On the use of deep learning for phase recoverycited by 20
  2. 2022Snapshot Multispectral Imaging Using a Diffractive Optical Networkcited by 16
  3. 2022Unidirectional Imaging using Deep Learning-Designed Materialscited by 13
  4. 2022Polarization Multiplexed Diffractive Computing: All-Optical Implementation of a Group of Linear Transformations Through a Polarization-Encoded Diffractive Networkcited by 10
  5. 2023Multispectral Quantitative Phase Imaging Using a Diffractive Optical Networkcited by 10
  6. 2023All-Optical Phase Conjugation Using Diffractive Wavefront Processingcited by 8
  7. 2022Diffractive Interconnects: All-Optical Permutation Operation Using Diffractive Networkscited by 6
  8. 2023All-optical image denoising using a diffractive visual processorcited by 6
  9. 2022All-optical image classification through unknown random diffusers using a single-pixel diffractive networkcited by 5
  10. 2022Analysis of Diffractive Neural Networks for Seeing Through Random Diffuserscited by 4
  11. 2022Time-lapse image classification using a diffractive neural networkcited by 4
  12. 2023Pyramid diffractive optical networks for unidirectional image magnification and demagnificationcited by 3
10 more
  1. 2024All-optical complex field imaging using diffractive processorscited by 2
  2. 2024Multiplexed all-optical permutation operations using a reconfigurable diffractive optical networkcited by 2
  3. 2024Multiplane Quantitative Phase Imaging Using a Wavelength-Multiplexed Diffractive Optical Processorcited by 2
  4. 2022Differentiable Microscopy Designs an All Optical Phase Retrieval Microscopecited by 1
  5. 2024Integration of Programmable Diffraction with Digital Neural Networkscited by 1
  6. 2024Coherence Awareness in Diffractive Neural Networkscited by 1
  7. 2025SP2RINT: Spatially-Decoupled Physics-Inspired Progressive Inverse Optimization for Scalable, PDE-Constrained Meta-Optical Neural Network Trainingcited by 1
  8. 2023QuATON: Quantization Aware Training of Optical Neuronscited by 0
  9. 2026Wavelength-multiplexed massively parallel diffractive optical information storage and image projectioncited by 0
  10. 2026Wavelength-Multiplexed 2D Beam Steering via a Passive Diffractive Networkcited by 0