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  1. Abstract

    We demonstrate in situ non-invasive relay imaging through a medium without inserting physical optical components. We show that a virtual optical graded-index (GRIN) lens can be sculpted in the medium using in situ reconfigurable ultrasonic interference patterns to relay images through the medium. Ultrasonic wave patterns change the local density of the medium to sculpt a graded refractive index pattern normal to the direction of light propagation, which modulates the phase front of light, causing it to focus within the medium and effectively creating a virtual relay lens. We demonstrate the in situ relay imaging and resolving of small features (22 µm) through a turbid medium (optical thickness = 5.7 times the scattering mean free path), which is normally opaque. The focal distance and the numerical aperture of the sculpted optical GRIN lens can be tuned by changing the ultrasonic wave parameters. As an example, we experimentally demonstrate that the axial focal distance can be continuously scanned over a depth of 5.4 mm in the modulated medium and that the numerical aperture can be tuned up to 21.5%. The interaction of ultrasonic waves and light can be mediated through different physical media, including turbid media, such as biological tissue, in which the ultrasonically sculpted GRIN lens can be used for relaying images of the underlying structures through the turbid medium, thus providing a potential alternative to implanting invasive endoscopes.

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  2. Free, publicly-accessible full text available May 29, 2024
  3. One of the open challenges in lensless imaging is understanding how well they resolve scenes in three dimensions. The measurement model underlying prior lensless imagers lacks special structures that facilitate deeper analysis; thus, a theoretical study of the achievable spatio-axial resolution has been lacking. This paper provides such a theoretical framework by analyzing a generalization of a mask-based lensless camera, where the sensor captures z-stacked measurements acquired by moving the sensor relative to an attenuating mask. We show that the z-stacked measurements are related to the scene’s volumetric albedo function via a three-dimensional convolutional operator. The specifics of this convolution, and its Fourier transform, allow us to fully characterize the spatial and axial resolving power of the camera, including its dependence on the mask. Since z-stacked measurements are a superset of those made by previously-studied lensless systems, these results provide an upper bound for their performance. We numerically evaluate the theory and its implications using simulations.

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  4. We exploit memory effect correlations in speckles for the imaging of incoherent fluorescent sources behind scattering tissue. These correlations are often weak when imaging thick scattering tissues and complex illumination patterns, both of which greatly limit the practicality of associated techniques. In this work, we introduce a spatial light modulator between the tissue sample and the imaging sensor and capture multiple modulations of the speckle pattern. We show that by correctly designing the modulation patterns and the associated reconstruction algorithm, statistical correlations in the measurements can be greatly enhanced. We exploit this to demonstrate the reconstruction of mega-pixel sized fluorescent patterns behind the scattering tissue.

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  5. Free, publicly-accessible full text available December 1, 2023
  6. Free, publicly-accessible full text available December 1, 2023
  7. Reconstructing and designing media with continuously-varying refractive index fields remains a challenging problem in computer graphics. A core difficulty in trying to tackle this inverse problem is that light travels inside such media along curves, rather than straight lines. Existing techniques for this problem make strong assumptions on the shape of the ray inside the medium, and thus limit themselves to media where the ray deflection is relatively small. More recently, differentiable rendering techniques have relaxed this limitation, by making it possible to differentiably simulate curved light paths. However, the automatic differentiation algorithms underlying these techniques use large amounts of memory, restricting existing differentiable rendering techniques to relatively small media and low spatial resolutions. We present a method for optimizing refractive index fields that both accounts for curved light paths and has a small, constant memory footprint. We use the adjoint state method to derive a set of equations for computing derivatives with respect to the refractive index field of optimization objectives that are subject to nonlinear ray tracing constraints. We additionally introduce discretization schemes to numerically evaluate these equations, without the need to store nonlinear ray trajectories in memory, significantly reducing the memory requirements of our algorithm. We use our technique to optimize high-resolution refractive index fields for a variety of applications, including creating different types of displays (multiview, lightfield, caustic), designing gradient-index optics, and reconstructing gas flows. 
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