Subwavelength Imaging using a Solid-Immersion Diffractive Optical Processor

no code implementations • 17 Jan 2024 • Jingtian Hu, Kun Liao, Niyazi Ulas Dinc, Carlo Gigli, Bijie Bai, Tianyi Gan, Xurong Li, Hanlong Chen, Xilin Yang, Yuhang Li, Cagatay Isil, Md Sadman Sakib Rahman, Jingxi Li, Xiaoyong Hu, Mona Jarrahi, Demetri Psaltis, Aydogan Ozcan

To resolve subwavelength features of an object, the diffractive imager uses a thin, high-index solid-immersion layer to transmit high-frequency information of the object to a spatially-optimized diffractive encoder, which converts/encodes high-frequency information of the input into low-frequency spatial modes for transmission through air.

Decoder

Physics-informed neural networks for diffraction tomography

no code implementations • 28 Jul 2022 • Amirhossein Saba, Carlo Gigli, Ahmed B. Ayoub, Demetri Psaltis

Our physics-informed neural networks can be generalized for any forward and inverse scattering problem.

Tomographic Reconstructions

Optical Diffraction Tomography based on 3D Physics-Inspired Neural Network (PINN)

no code implementations • 10 Jun 2022 • Ahmed B. Ayoub, Amirhossein Saba, Carlo Gigli, Demetri Psaltis

The 3D NN starts with an initial guess for the 3D RI reconstruction (i. e. Born, or Rytov) and aims at reconstructing better 3D reconstruction based on an error function.

3D Reconstruction