Single-pixel transmission matrix recovery via two-photon fluorescence.

Imaging at depth in opaque materials has long been a challenge. Recently, wavefront shaping has enabled notable advance for deep imaging. Nevertheless, most noninvasive wavefront-shaping methods require cameras, lack the sensitivity for deep imaging under weak optical signals, or can only focus on a single "guidestar." Here, we retrieve the transmission matrix (TM) noninvasively using two-photon fluorescence exploiting a single-pixel detection combined with a computational framework, allowing to achieve single-target focus on multiple guidestars spread beyond the memory effect range. In addition, if we assume that memory effect correlations exist in the TM, we are able to substantially reduce the number of measurements needed.

Physics-based neural network for non-invasive control of coherent light in scattering media.

Optical imaging through complex media, such as biological tissues or fog, is challenging due to light scattering. In the multiple scattering regime, wavefront shaping provides an effective method to retrieve information; it relies on measuring how the propagation of different optical wavefronts are impacted by scattering. Based on this principle, several wavefront shaping techniques were successfully developed, but most of them are highly invasive and limited to proof-of-principle experiments. Here, we propose to use a neural network approach to non-invasively characterize and control light scattering inside the medium and also to retrieve information of hidden objects buried within it. Unlike most of the recently-proposed approaches, the architecture of our neural network with its layers, connected nodes and activation functions has a true physical meaning as it mimics the propagation of light in our optical system. It is trained with an experimentally-measured input/output dataset built from a series of incident light patterns and corresponding camera snapshots. We apply our physics-based neural network to a fluorescence microscope in epi-configuration and demonstrate its performance through numerical simulations and experiments. This flexible method can include physical priors and we show that it can be applied to other systems as, for example, non-linear or coherent contrast mechanisms.

Artifacts in optical projection tomography due to refractive-index mismatch: model and correction.

Optical projection tomography (OPT) is a powerful tool for three-dimensional (3D) imaging of mesoscopic samples. While it is able to achieve resolution of a few tens of microns over a sample volume of several cubic centimeters, the reconstructed images often suffer from artifacts caused by inaccurate calibration. In this work, we focus on the refractive-index mismatch between the sample and the surrounding medium. We derive a 3D cone-beam forward model of OPT that approximates the effect of refractive-index mismatch. We then implement a fast and efficient reconstruction method to correct for the induced seagull-shaped artifacts on experimental images of fluorescent beads.

Salt-Inducible Kinase 3 Promotes Vascular Smooth Muscle Cell Proliferation and Arterial Restenosis by Regulating AKT and PKA-CREB Signaling.

Objective: Arterial restenosis is the pathological narrowing of arteries after endovascular procedures, and it is an adverse event that causes patients to experience recurrent occlusive symptoms. Following angioplasty, vascular smooth muscle cells (SMCs) change their phenotype, migrate, and proliferate, resulting in neointima formation, a hallmark of arterial restenosis. SIKs (salt-inducible kinases) are a subfamily of the AMP-activated protein kinase family that play a critical role in metabolic diseases including hepatic lipogenesis and glucose metabolism. Their role in vascular pathological remodeling, however, has not been explored. In this study, we aimed to understand the role and regulation of SIK3 in vascular SMC migration, proliferation, and neointima formation. Approach and Results: We observed that SIK3 expression was low in contractile aortic SMCs but high in proliferating SMCs. It was also highly induced by growth medium in vitro and in neointimal lesions in vivo. Inactivation of SIKs significantly attenuated vascular SMC proliferation and up-regulated p21CIP1 and p27KIP1. SIK inhibition also suppressed SMC migration and modulated actin polymerization. Importantly, we found that inhibition of SIKs reduced neointima formation and vascular inflammation in a femoral artery wire injury model. In mechanistic studies, we demonstrated that inactivation of SIKs mainly suppressed SMC proliferation by down-regulating AKT (protein kinase B) and PKA (protein kinase A)-CREB (cAMP response element-binding protein) signaling. CRTC3 (CREB-regulated transcriptional coactivator 3) signaling likely contributed to SIK inactivation-mediated antiproliferative effects. Conclusions: These findings suggest that SIK3 may play a critical role in regulating SMC proliferation, migration, and arterial restenosis. This study provides insights into SIK inhibition as a potential therapeutic strategy for treating restenosis in patients with peripheral arterial disease.

Accelerating ptychographic reconstructions using spectral initializations.

Ptychography is a promising phase retrieval technique for label-free quantitative phase imaging. Recent advances in phase retrieval algorithms witnessed the development of spectral methods to accelerate gradient descent algorithms. Using spectral initializations on experimental data, for the first time, we report three times faster ptychographic reconstructions than with a standard gradient descent algorithm and improved resilience to noise. Coming at no additional computational cost compared to gradient-descent-based algorithms, spectral methods have the potential to be implemented in large-scale iterative ptychographic algorithms.

Non-invasive focusing and imaging in scattering media with a fluorescence-based transmission matrix.

In biological microscopy, light scattering represents the main limitation to image at depth. Recently, a set of wavefront shaping techniques has been developed in order to manipulate coherent light in strongly disordered materials. The Transmission Matrix approach has shown its capability to inverse the effect of scattering and efficiently focus light. In practice, the matrix is usually measured using an invasive detector or low-resolution acoustic guide stars. Here, we introduce a non-invasive and all-optical strategy based on linear fluorescence to reconstruct the transmission matrices, to and from a fluorescent object placed inside a scattering medium. It consists in demixing the incoherent patterns emitted by the object using low-rank factorizations and phase retrieval algorithms. We experimentally demonstrate the efficiency of this method through robust and selective focusing. Additionally, from the same measurements, it is possible to exploit memory effect correlations to image and reconstruct extended objects. This approach opens up a new route towards imaging in scattering media with linear or non-linear contrast mechanisms.

Non-invasive single-shot recovery of a point-spread function of a memory effect based scattering imaging system.

Accessing the point-spread function (PSF) of a complex optical system is important for a variety of imaging applications. However, placing an invasive point source is often impractical, and estimating it blindly with multiple frames is slow and requires a complex nonlinear optimization. Here, we introduce a simple single-shot method to noninvasively recover the accurate PSF of an isoplanatic imaging system, in the context of multiple light scattering. Our approach is based on the reconstruction of any unknown sparse hidden object using the autocorrelation imaging technique, followed by a deconvolution with a blur kernel derived from the statistics of a speckle pattern. A deconvolution on the camera image then retrieves the accurate PSF of the system, enabling further imaging applications. We demonstrate numerically and experimentally the effectiveness of this approach compared to previous deconvolution techniques.

Imaging through a thin scattering layer and jointly retrieving the point-spread-function using phase-diversity.

Recently introduced angular-memory-effect based techniques enable non-invasive imaging of objects hidden behind thin scattering layers. However, both the speckle-correlation and the bispectrum analysis are based on the statistical average of large amounts of speckle grains, which determines that they can hardly access the important information of the point-spread-function (PSF) of a highly scattering imaging system. Here, inspired by notions used in astronomy, we present a phase-diversity speckle imaging scheme, based on recording a sequence of intensity speckle patterns at various imaging planes, and experimentally demonstrate that in addition to being able to retrieve the image of hidden objects, we can also simultaneously estimate the pupil function and the PSF of a highly scattering imaging system without any guide-star nor reference.

Experimental robustness of Fourier ptychography phase retrieval algorithms.

Fourier ptychography is a new computational microscopy technique that provides gigapixel-scale intensity and phase images with both wide field-of-view and high resolution. By capturing a stack of low-resolution images under different illumination angles, an inverse algorithm can be used to computationally reconstruct the high-resolution complex field. Here, we compare and classify multiple proposed inverse algorithms in terms of experimental robustness. We find that the main sources of error are noise, aberrations and mis-calibration (i.e. model mis-match). Using simulations and experiments, we demonstrate that the choice of cost function plays a critical role, with amplitude-based cost functions performing better than intensity-based ones. The reason for this is that Fourier ptychography datasets consist of images from both brightfield and darkfield illumination, representing a large range of measured intensities. Both noise (e.g. Poisson noise) and model mis-match errors are shown to scale with intensity. Hence, algorithms that use an appropriate cost function will be more tolerant to both noise and model mis-match. Given these insights, we propose a global Newton's method algorithm which is robust and accurate. Finally, we discuss the impact of procedures for algorithmic correction of aberrations and mis-calibration.