Optical Imaging

Imaging with multimode fibers



When images pass through optical fibers they become scrambled due to the different propagation velocities of their spatial modes. As a result of this, the different modes interfere on exiting from the fiber to produce a specular pattern. Research in the optics laboratory has focused on recovering the input images from their corresponding speckle patterns using deep neural networks. In particular, we have studied the effects of wavelength drift, and the difference between intensity only and holographic recording of the speckles on the reconstruction results. Work has also being carried out on reconstructing images obtained through multicore optical fibers using deep-learning techniques for the development of novel endoscopic microscopes.

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Optical diffraction tomography

Solving the missing cone problem in optical diffraction tomography (ODT)


Optical diffraction tomography (ODT) provides us with the 3D refractive index (RI) distributions of transparent samples by acquiring 2D holograms from multiple angles. Inverse models are able to retrieve the 3D distributions from those 2D projections. However, the final reconstruction suffer from what is called “missing cone problem” due to the limited numerical aperture (NA) of the imaging system. In our group, we aim to solve this problem by 2 approaches. The first is a model based iterative reconstruction scheme. The second approach is based on neural networks.

Intensity-only optical diffraction tomography (ODT)



Instead of using holographic data to reconstruct the 3D RI distribution of the sample using inverse models, inverse models were directly applied on 2D intensity projections. Although the final reconstruction does not explicitly represent the 3D RI distribution of the samples, the high frequency features of the sample were more pronounced as compared to 3D reconstructions using 2D holographic data acquired from different projections. This property can be used to localize nanoparticles such as lipids inside a biological sample. In one of our collaborations we used these reconstructions to investigate the presence of nanoparticles on the membrane of immune T-cells.

Polarization sensitive optical diffraction tomography (ODT)



Polarization of light has been widely used as a contrast mechanism in many imaging modalities. In our group we reformulated inverse models to reconstruct the RI tensor of the samples which is directly linked to the birefringence of the sample. The off-diagonal components of the RI tensor reconstruction convey additional information that is not available in either conventional scalar ODT or 2D polarization microscopy. We used those vector-based models to estimate the birefringence of biological samples including human muscle tissues.

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