Optimization of focusing through scattering media using the continuous sequential algorithm

Light scattering control with the two-step focusing method based on neural networks and multi-pixel coding

Focusing light through scattering media is essential for high-resolution optical imaging and deep penetration. Here, a two-step focusing method based on neural networks (NNs) and multi-pixel coding is proposed to achieve high-quality focusing with theoretical maximum enhancement. In the first step, a single-layer neural network (SLNN) is used to obtain the initial mask, which can be used to focus with a moderate enhancement. In the second step, we use multi-pixel coding to encode the initial mask. The coded masks and their corresponding speckle patterns are used to train another SLNN to get the final mask and achieve high-quality focusing. In this experiment, for a mask of 16 × 16 modulation units, in the case of using 8 pixels in a modulation unit, focus with the enhancement of 40.3 (only 0.44 less than the theoretical value) has been achieved with 3000 pictures (1000 pictures in the first step and 2000 pictures in the second step). Compared with the case of employing only the initial mask and the direct multi-pixel encoded mask, the enhancement is increased by 220% and 24%. The proposed method provides a new idea for improving the focusing effect through the scattering media using NNs.

Hybrid optimization algorithm based on neural networks and its application in wavefront shaping

The scattering effect of turbid media can lead to optical wavefront distortion. Focusing light through turbid media can be achieved using wavefront shaping techniques. Intelligent optimization algorithms and neural network algorithms are two powerful types of algorithms in the field of wavefront shaping but have their advantages and disadvantages. In this paper, we propose a new hybrid algorithm that combines the particle swarm optimization algorithm (PSO) and single-layer neural network (SLNN) to achieve the complementary advantages of both. A small number of training sets are used to train the SLNN to obtain preliminary focusing results, after which the PSO continues to optimize to the global optimum. The hybrid algorithm achieves faster convergence and higher enhancement than the PSO, while reducing the size of training samples required for SLNN training. SLNN trained with 1700 training sets can speed up the convergence of the PSO by about 50% and boost the final enhancement by about 24%. This hybrid algorithm will be of great significance in fields such as biomedicine and particle manipulation.

Coherent anti-Stokes Raman scattering imaging of microcalcifications associated with breast cancer

Chemical imaging of calcifications was demonstrated in the depth of a tissue. Using long wavelength excitation, broadband coherent anti-Stokes Raman scattering and hierarchical cluster analysis, imaging and chemical analysis were performed 2 mm below the skin level in a model system. Applications to breast cancer diagnostics and imaging are discussed together with the methods to further extend the depth and improve the spatial resolution of chemical imaging.

Adaptive optics approach to surface-enhanced Raman scattering

Surface-enhanced Raman scattering (SERS) spectroscopy is a popular technique for detecting chemicals in small quantities. Rough metallic surfaces with nanofeatures are some of the most widespread and commercially successful substrates for efficient SERS measurements. A rough metallic surface creates a high-density random distribution of so-called "hot spots" with local optical field enhancement causing Raman signal to increase. In this Letter, we revisit the classic SERS experiment [Surf. Sci.158, 229 (1985)SUSCAS0039-602810.1016/0039-6028(85)90297-3] with rough metallic surfaces covered by a thin layer of copper phthalocyanine molecules. As a modification to the classic configuration, we apply an adaptive wavefront correction of a laser beam profile. As a result, we demonstrate an increase in brightness of local SERS hot spots and redistribution of Raman signal over the substrate area. We hypothesize that the improvement is due to optimal coupling of the shaped laser beam to the random plasmonic nanoantenna configurations. We show that the proposed adaptive-SERS modification is independent of the exact structure of the surface roughness and topography, works with many rough surfaces, and gives brighter Raman hot spots in comparison with conventional SERS measurements. We prove that the adaptive SERS is a powerful instrument for improving SERS sensitivity.

Coherent Raman Generation Controlled by Wavefront Shaping

We investigate the possibility of tailoring coherent Raman generated spectra via adaptive wavefront optimization. Our technique combines a spatial light modulator and a spectrometer providing a feedback loop. The algorithm is capable of controlling the Raman generation, producing broader spectra and an improved overall efficiency, and increasing the intensity of high-order sidebands. Moreover, by wavefront optimization we can extend the generated spectra towards the blue spectral region and increase the total power of generated sidebands. Mutual coherence and equal frequency separation of the multiple Raman sidebands are of interest for the synthesis of ultrashort light pulses with the total spectral bandwidth extending over ultraviolet, visible and near-infrared wavelengths.

Enhanced coupling of light into a turbid medium through microscopic interface engineering

There are many optical detection and sensing methods used today that provide powerful ways to diagnose, characterize, and study materials. For example, the measurement of spontaneous Raman scattering allows for remote detection and identification of chemicals. Many other optical techniques provide unique solutions to learn about biological, chemical, and even structural systems. However, when these systems exist in a highly scattering or turbid medium, the optical scattering effects reduce the effectiveness of these methods. In this article, we demonstrate a method to engineer the geometry of the optical interface of a turbid medium, thereby drastically enhancing the coupling efficiency of light into the material. This enhanced optical coupling means that light incident on the material will penetrate deeper into (and through) the medium. It also means that light thus injected into the material will have an enhanced interaction time with particles contained within the material. These results show that, by using the multiple scattering of light in a turbid medium, enhanced light-matter interaction can be achieved; this has a direct impact on spectroscopic methods such as Raman scattering and fluorescence detection in highly scattering regimes. Furthermore, the enhanced penetration depth achieved by this method will directly impact optical techniques that have previously been limited by the inability to deposit sufficient amounts of optical energy below or through highly scattering layers.

Wavefront shaping enhanced Raman scattering in a turbid medium

Spontaneous Raman scattering is a powerful tool for chemical sensing and imaging but suffers from a weak signal. In this Letter, we present an application of adaptive optics to enhance the Raman scattering signal detected through a turbid, optically thick material. This technique utilizes recent advances in wavefront shaping techniques for focusing light through a turbid media and applies them to chemical detection to achieve a signal enhancement with little sacrifice to the overall simplicity of the experimental setup. With this technique, we demonstrate an enhancement in the Raman signal from titanium dioxide particles through a highly scattering material. This technique may pave the way to label-free tracking using the optical memory effect.