High-contrast light focusing through scattering media with multi-pixel encoding

Abstract

Realizing a high-contrast anti-scattering light focusing by using a spatial light modulation such as a digital micromirror device (DMD) demands a robust optimizer in the process of wavefront shaping. Genetic algorithm (GA) as a common practice can easily be stuck into the inferior local minima. Here, we combined GA with encoding neighboring pixels of DMD to circumvent the inferior local minima. Simulations and experiments have demonstrated that our method could greatly increase the anti-scattering capability when compared with the conventional GA method. This work could be an important step towards deep tissue noninvasive optical imaging, optogenetics, and photodynamic therapy.

Wavefront shaping: A versatile tool to conquer multiple scattering in multidisciplinary fields

“…20 However, in the 1980s, researchers started to notice that the seemingly random scattering events were actually deterministic within the speckle decorrelation window. 21 , 22 In 2007, Vellekoop and Mosk proposed a game-changing solution called wavefront shaping (WFS), with which the optical scattering-induced distortions can be precompensated by iteratively optimizing the input wavefront 23 , 24 , 25 , 26 , 27 , 28 or time-reversing the scattering wavefront. 29 , 30 , 31 , 32 , 33 Furthermore, it was shown that the optical propagation through a complex medium can be systematically described by measuring the transmission matrix (TM) of the medium, 34 , 35 , 36 , 37 , 38 , 39 , 40 which enables the manipulation of an incident wavefront for any desired output.…”

Optimal efficiency of focusing diffused light through scattering media with iterative wavefront shaping

“…In this technique, the wavefront of incident light is iteratively modulated by a spatial light modulator (SLM) according to the feedback signals from a detector (e.g., camera or photodetector) placed behind the scattering medium or a guidestar (e.g., fluorescent or photoacoustic emission as a virtual guidestar 40,41 ) within the scattering medium; hence, the optical distortions can be compensated and an optical focus or the desired output field can be obtained at the target location. Several metaheuristic optimization algorithms, such as genetic algorithm (GA), [17][18][19][20][21] particle swarm optimization (PSO), [22][23][24][25][26] simulated annealing algorithm (SA), 27,28 bat algorithm (BA), 31 ant colony optimization (ACO), 32 and separable natural evolution strategies (SNES), 33 have been demonstrated for successful optical focusing inside/through scattering media. Aiming for faster and better optimization results, researchers have improved different algorithms primarily in three ways: optimizing parameters, introducing variants of the algorithms, such as microgenetic algorithm (μGA), 19 particle swarm optimization with mutation, 26 and improved ant colony optimization (IACO); 32 and exploiting hybrid algorithms, such as parameter-free algorithm (PFA), a combination of genetic algorithm and bat algorithm, 30 and Genetic Neural Network (GeneNN), a hybrid of GA and deep neural networks.…”

Multi-focus manipulation system based on separable natural evolution strategy aberration self-calibration

“…These iterative algorithms have been applied in holographic microscopy imaging, anti-scattering light focusing, and other optical systems. [15][16][17] These methods successfully search and compensate for complex aberrations such as distortion caused by strong scattering 18) and achieve high-quality controllable multi-point focusing. 19) However, these state-of-the-art algorithms have limited global search capability and are sensitive to the initial condition and the local minima.…”