Wide-field, high-resolution reconstruction in computational multi-aperture miniscope using a Fourier neural network

Lensless imaging with a programmable Fresnel zone aperture

Optical imaging has long been dominated by traditional lens-based systems that, despite their success, are inherently limited by size, weight, and cost. Lensless imaging seeks to overcome these limitations by replacing lenses with thinner, lighter, and cheaper optical modulators and reconstructing images computationally, while facing trade-offs in image quality, artifacts, and flexibility inherent in traditional static modulation. Here, we propose a lensless imaging method with programmable Fresnel zone aperture (FZA), termed LIP. With a commercial liquid crystal display, we designed an integrated LIP module and demonstrated its capability of high-quality artifact-free reconstruction through dynamic modulation and offset-FZA parallel merging. Compared to static-modulation approaches, LIP achieves a 2.5× resolution enhancement and a 3 decibels improvement in signal-to-noise ratio in "static mode" while maintaining an interaction frame rate of 15 frames per second in "dynamic mode." Experimental results demonstrate LIP's potential as a miniaturized platform for versatile advanced imaging tasks like virtual reality and human-computer interaction.

V-shaped PSF for 3D imaging over an extended depth of field in wide-field microscopy

Single-shot 3D optical microscopy that can capture high-resolution information over a large volume has broad applications in biology. Existing 3D imaging methods using point-spread-function (PSF) engineering often have limited depth of field (DOF) or require custom and often complex design of phase masks. We propose a new, to the best of our knowledge, PSF approach that is easy to implement and offers a large DOF. The PSF appears to be axially V-shaped, engineered by replacing the conventional tube lens with a pair of axicon lenses behind the objective lens of a wide-field microscope. The 3D information can be reconstructed from a single-shot image using a deep neural network. Simulations in a 10× magnification wide-field microscope show the V-shaped PSF offers excellent 3D resolution (<2.5 µm lateral and ∼15 µm axial) over a ∼350 µm DOF at a 550 nm wavelength. Compared to other popular PSFs designed for 3D imaging, the V-shaped PSF is simple to deploy and provides high 3D reconstruction quality over an extended DOF.

EventLFM: event camera integrated Fourier light field microscopy for ultrafast 3D imaging

Ultrafast 3D imaging is indispensable for visualizing complex and dynamic biological processes. Conventional scanning-based techniques necessitate an inherent trade-off between acquisition speed and space-bandwidth product (SBP). Emerging single-shot 3D wide-field techniques offer a promising alternative but are bottlenecked by the synchronous readout constraints of conventional CMOS systems, thus restricting data throughput to maintain high SBP at limited frame rates. To address this, we introduce EventLFM, a straightforward and cost-effective system that overcomes these challenges by integrating an event camera with Fourier light field microscopy (LFM), a state-of-the-art single-shot 3D wide-field imaging technique. The event camera operates on a novel asynchronous readout architecture, thereby bypassing the frame rate limitations inherent to conventional CMOS systems. We further develop a simple and robust event-driven LFM reconstruction algorithm that can reliably reconstruct 3D dynamics from the unique spatiotemporal measurements captured by EventLFM. Experimental results demonstrate that EventLFM can robustly reconstruct fast-moving and rapidly blinking 3D fluorescent samples at kHz frame rates. Furthermore, we highlight EventLFM's capability for imaging of blinking neuronal signals in scattering mouse brain tissues and 3D tracking of GFP-labeled neurons in freely moving C. elegans. We believe that the combined ultrafast speed and large 3D SBP offered by EventLFM may open up new possibilities across many biomedical applications.