Scattering phenomena affect light propagation through any kind of medium from free space to biological tissues. Finding appropriate strategies to increase the robustness to scattering is the common requirement in developing both communication protocols and imaging systems. Recently, structured light has attracted attention due to its seeming scattering resistance in terms of transmissivity and spatial behavior. Moreover, correlation between optical polarization and orbital angular momentum (OAM), which characterizes the so-called vector vortex beams (VVBs) states, seems to allow for the preservation of the polarization pattern. We extend the analysis by investigating both the spatial features and the polarization structure of vectorial optical vortexes propagating in scattering media with different concentrations. Among the observed features, we find a sudden swift decrease in contrast ratio for Gaussian, OAM, and VVB modes for concentrations of the adopted scattering media exceeding 0.09%. Our analysis provides a more general and complete study on the propagation of structured light in dispersive and scattering media.

Diffuse optical tomography using deep learning is an emerging technology that has found impressive medical diagnostic applications. However, creating an optical imaging system that uses visible and near-infrared (NIR) light is not straightforward due to photon absorption and multi-scattering by tissues. The high distortion levels caused due to these effects make the image reconstruction incredibly challenging. To overcome these challenges, various techniques have been proposed in the past, with varying success. One of the most successful techniques is the application of deep learning algorithms in diffuse optical tomography. This article discusses the current state-of-the-art diffuse optical tomography systems and comprehensively reviews the deep learning algorithms used in image reconstruction. This article attempts to provide researchers with the necessary background and tools to implement deep learning methods to solve diffuse optical tomography.

A major challenge in use of the optical spectrum for communication and imaging applications is the scattering of light as it passes through diffuse media. Recent studies indicate that light beams with orbital angular momentum (OAM) can penetrate deeper through diffuse media than simple Gaussian beams. To the best knowledge of the authors, in this paper we describe for the first time an experiment examining transmission of OAM beams through biological tissue with thickness of up to a few centimeters, and for OAM modes reaching up to 20. Our results indicate that OAM beams do indeed show a higher transmittance relative to Gaussian beams, and that the greater the OAM, the higher the transmittance also up to 20, Our results extend measured results to highly multi scattering media and indicate that at 2.6 cm tissue thickness for OAM of order 20, we measure nearly 30% more power in comparison to a Gaussian beam. In addition, we develop a mathematical model describing the improved permeability. This work shows that OAM beams can be a valuable contribution to optical wireless communication (OWC) for medical implants, optical biological imaging, as well as recent innovative applications of medical diagnosis.

This study aims to explore the experiences and accounts of Israeli gay fathers through surrogacy, with regard to contextual elements in general and geographical location in particular. Fourteen Jewish-Israeli gay fathers who became parents through surrogacy abroad were interviewed. Half of the participants live in Tel Aviv, and the other half live in the country’s outlying areas in villages or relatively small towns. In-depth semi-structured interviews were conducted, recorded, transcribed, and thematically analyzed. The analysis yielded three themes: (a) between “periphery” and “center,” which reflects a spatial binary as expressed in the fathers’ accounts; (b) realms of belonging, which focuses on the challenge the fathers pose to the binary periphery/center distinction; and (c) movement toward inclusion, which explores the fathers’ constant movement toward belonging within the different spatial realms. Our findings represent fatherhood as a spatial-contextual phenomenon.

Optical imaging through diffuse media is a challenging issue and has attracted applications in many fields such as biomedical imaging, non-destructive testing, and computer-assisted surgery. However, light interaction with diffuse media leads to multiple scattering of the photons in the angular and spatial domain, severely degrading the image reconstruction process. In this article, a novel method to image through diffuse media using multiple modes of vortex beams and a new deep learning network named “LGDiffNet” is derived. A proof-of-concept numerical simulation is conducted using this method, and the results are experimentally verified. In this technique, the multiple modes of Gaussian and Laguerre-Gaussian beams illuminate the displayed digits dataset number, and the beams are then propagated through the diffuser before being captured on the beam profiler. Furthermore, we investigated whether imaging through diffuse media using multiple modes of vortex beams instead of Gaussian beams improves the imaging system's imaging capability and enhances the network's reconstruction ability. Our results show that illuminating the diffuser using vortex beams and employing the “LGDiffNet” network provides enhanced image reconstruction compared to existing modalities. An enhancement of ~ 1 dB, in terms of PSNR, is achieved using this method when a highly scattering diffuser of grit 220 and width 2 mm (7.11 times the mean free path) is used. No additional optimizations or reference beams were used in the imaging system, revealing the robustness of the “LGDiffNet” network and the adaptability of the imaging system for practical applications in medical imaging.