This PDF file contains the front matter associated with SPIE Proceedings Volume 12851, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

In the recent years, numerous adaptive optics techniques have emerged to address optical aberrations in fluorescence microscopy imaging. However, many existing methods involve complex hardware implementations or lengthy iterative algorithms that may induce photo-damage to the sample. Our study proposes an innovative approach centered around a novel detector array capable of potentially capturing the probed sample in a single acquisition. Our solution is gentle on the sample and applicable to any laser scanning microscope equipped with a detector array. We demonstrate that the multi-dimensional dataset obtained using the detector array inherently encodes information about optical aberrations. Finally, we propose a convolutional neural network approach to decode these optical aberrations in real-time and with high accuracy, establishing the foundation for a new class of adaptive optics laser-scanning microscopy methods.

By measuring and correcting sample-induced aberrations, adaptive optics (AO) enables noninvasive imaging of subcellular structures in living organisms with two-photon (2P) fluorescence microscopy. We will introduce CoCoA-2P, a self-supervised machine-learning algorithm capable of simultaneously estimating aberrations and recovering 3D structural information from a single 2P image stack without requiring external training datasets. We will showcase the applications of CoCoA-2P for high-resolution in vivo structural imaging of the mouse brain and eye lenses.

The multiple scattering of light makes materials opaque and obstructs imaging. Wavefront shaping can reverse the scattering process, but imaging with physical wavefront shaping has severe deficiencies such as requiring physical guidestars, limited within a small isoplanatic patch, restricted to planar targets outside the scattering media, and slow wavefront updates due to the hardware. Here, we introduce scattering matrix tomography (SMT): measure the hyperspectral scattering matrix of the sample, use it to digitally scan a synthesized confocal spatiotemporal focus and construct a volumetric image of the sample, and then use the synthesized image as many virtual guidestars to digitally optimize the pulse shape, input wavefront, and output wavefront to compensate for aberrations and scattering. The virtual feedback dispenses with physical guidestars and enables hardware-free spatiotemporal wavefront corrections across arbitrarily many isoplanatic patches. We demonstrate SMT with sub-micron diffraction-limited lateral resolution and one-micron bandwidth-limited axial resolution at one millimeter beneath ex vivo mouse brain tissue and inside a dense colloid, where all existing imaging methods fail due to the overwhelming multiple scattering. SMT translates imaging and wavefront shaping into a computational problem. It is noninvasive and label-free, provides multi-isoplanatic volumetric images inside and outside the scattering media, and can be applied to medical imaging, device inspection, biological science, and colloidal physics.

We present a new liquid crystal-based device for correction of spherical aberration, which is commonly observed in microscopy and related methods. The device is significantly larger than previous direct laser written aberration correctors, measuring 1 mm across. The device operates in transmission mode for easy integration into the optical path and is capable of continuous greyscale tuning of up to a total amplitude of 2π rad. This device could present a cost effective and simpler to use alternative to traditional wavefront modulation technologies used in adaptive optics.

Mitochondria are extremely important organelles in the regulation of bone marrow and brain activity. However, live imaging of these subcellular features with high resolution in scattering tissues like brain or bone has proven challenging. In this study, we create a next-generation two-photon fluorescence microscope that leverages low-order wavefront correction by Shack-Hartmann wavefront sensor based on different metrics to achieve fast imaging of subcellular organelles of highly scattering living mice. Metrics include maximum intensity, minimum full width at half maximum (FWHM), and maximum energy of the point spread function (PSF), enabling accuracy and robustness of sensorless correction of the system. Using AO increases the fluorescence intensity and FWHM of the PSF and achieves fast imaging of subcellular organelles with 400nm resolution through 85 μm of highly scattering tissue. This study demonstrates a promising tool for imaging mitochondria and other organelles in optically distorting biological environments, which could facilitate the study of a variety of diseases connected to mitochondrial morphology and activity in a range of biological tissues.

Multiphoton microscopy applied in bone tissue is susceptible to optical aberrations caused by heterogeneity in refractive index. Optical clearing can be applied to alleviate some of these aberrations, but it is invasive and causes deviations from normal tissue biology. We recover diffraction limited imaging by means of a high spatial frequency digital micromirror device (DMD), and binary wavefront modulation. A genetic algorithm optimizes the DMD pattern by evaluating the intensity of the Second Harmonic Generation point spread function measured in the bone sample. We present a five-fold GFP intensity improvement, and a 29% spatial resolution increase within an ex vivo mouse sample.

Established techniques for measuring the transmission matrix (TM) of a multimode fiber (MMF) allow for spot scanning at the distal end of the fiber through phase control at the proximal end, enabling ultrathin medical endoscopes and other applications that benefit from controllable light fields in MMF. Adding this capability to fibers utilized for other applications allows imaging to be performed within these areas. One outstanding limitation of this technology is the need to re-calibrate the fiber upon bending or other environmental perturbation. Here, we demonstrate a modified shape-sensor fiber that allows both shape sensing and imaging within the same fiber. In addition to permitting an image at the end of a shape sensor probe, the unification of these two technologies opens up the possibility of using the reconstructed fiber shape to mathematically update the calibration of the imaging waveguide in a dynamic environment, as has been proposed in the prior literature. Creating a robust method for maintaining knowledge of the fiber’s TM as the fiber is manipulated is critical for clinical deployment of this technology.