High-gain and high-speed wavefront shaping through scattering media

Theoretical framework for calibrating the depth-dependent optical scattering in layered human skin using spatially offset measurements

Spatially offset spectroscopy offers an alternative non-invasive method for enabling deep probing of structures and chemical molecules, which is clinically significant for the characterization of chemical and physical alterations in human skin. However, a more precise depth-resolved quantification using the spatially offset measurements still remains a challenge due to the mixed inhomogeneous scattering. Herein, we report a Monte-Carlo-based quantification modeling platform combined with a novel, to the best of our knowledge, scattering spectrum decomposition method to explore the depth-dependent optical scattering contributions in human skin. In the simplified modeling, human skin was empirically set to be composed of multiple layers, and each layer possessed different photon weights for the spatially offset scattering intensity measurements. The modeling results of photon transportation in-and-out of the layered skin substantially discovered that the layer-dependent scattering contribution was compositely encoded into the spatially offset measurements and varied with the illumination incidence angle. For calibrating the layer-dependent scattering contribution, a modified nonlinear independent component processing algorithm was applied to the spatially offset measurements by decomposing the photon weights of each layer. The calibration results figured out the major scattering contribution of each layer along the offset axis under different incidence angles, which were consistent with previous experimental observations. The proposed theoretical framework establishes a feasible approach for spatially offset optical spectroscopies enabling non-invasive quantitative A-line characterization of the concentrations of skin components.

High-fidelity and high-speed wavefront shaping by leveraging complex media

High-precision light manipulation is crucial for delivering information through complex media. However, existing spatial light modulation devices face a fundamental speed-fidelity tradeoff. Digital micromirror devices have emerged as a promising candidate for high-speed wavefront shaping but at the cost of compromised fidelity due to the limited control degrees of freedom. Here, we leverage the sparse-to-random transformation through complex media to overcome the dimensionality limitation of spatial light modulation devices. We demonstrate that pattern compression by sparsity-constrained wavefront optimization allows sparse and robust wavefront representations in complex media, improving the projection fidelity without sacrificing frame rate, hardware complexity, or optimization time. Our method is generalizable to different pattern types and complex media, supporting consistent performance with up to 89% and 126% improvements in projection accuracy and speckle suppression, respectively. The proposed optimization framework could enable high-fidelity high-speed wavefront shaping through different scattering media and platforms without changes to the existing holographic setups, facilitating a wide range of physics and real-world applications.

All-optical phase conjugation using diffractive wavefront processing

Optical phase conjugation (OPC) is a nonlinear technique used for counteracting wavefront distortions, with applications ranging from imaging to beam focusing. Here, we present a diffractive wavefront processor to approximate all-optical phase conjugation. Leveraging deep learning, a set of diffractive layers was optimized to all-optically process an arbitrary phase-aberrated input field, producing an output field with a phase distribution that is the conjugate of the input wave. We experimentally validated this wavefront processor by 3D-fabricating diffractive layers and performing OPC on phase distortions never seen during training. Employing terahertz radiation, our diffractive processor successfully performed OPC through a shallow volume that axially spans tens of wavelengths. We also created a diffractive phase-conjugate mirror by combining deep learning-optimized diffractive layers with a standard mirror. Given its compact, passive and multi-wavelength nature, this diffractive wavefront processor can be used for various applications, e.g., turbidity suppression and aberration correction across different spectral bands.

Non-Invasive Self-Adaptive Information States' Acquisition inside Dynamic Scattering Spaces

Pushing the information states' acquisition efficiency has been a long-held goal to reach the measurement precision limit inside scattering spaces. Recent studies have indicated that maximal information states can be attained through engineered modes; however, partial intrusion is generally required. While non-invasive designs have been substantially explored across diverse physical scenarios, the non-invasive acquisition of information states inside dynamic scattering spaces remains challenging due to the intractable non-unique mapping problem, particularly in the context of multi-target scenarios. Here, we establish the feasibility of non-invasive information states' acquisition experimentally for the first time by introducing a tandem-generated adversarial network framework inside dynamic scattering spaces. To illustrate the framework's efficacy, we demonstrate that efficient information states' acquisition for multi-target scenarios can achieve the Fisher information limit solely through the utilization of the external scattering matrix of the system. Our work provides insightful perspectives for precise measurements inside dynamic complex systems.

Widefield functional speckle-correlation optical scattering mesoscopy toward hemodynamic imaging

Speckle-correlation optical scattering imaging (SCOSI) has shown the potential for non-invasive biomedical diagnostic applications, which directly utilizes the scattering patterns to reconstruct the deep and non-line-of-sight objects. However, the course of the translation of this technique to preclinical biomedical imaging applications has been postponed by the following two facts: 1) the field of view of SCOSI was significantly limited by the optical memory effect, and 2) the molecular-tagged functional imaging of the biological tissues remains largely unexplored. In this work, a proof-of-concept design of the first-generation widefield functional SCOSI (WF-SCOSI) system was presented for simultaneously achieving mesoscopic mapping of fluid morphology and flow rate, which was realized by implementing the concepts of scanning synthesis and fluorescence scattering flowmetry. The ex vivo imaging results of the fluorescence-labeled large-scale blood vessel network phantom underneath the strong scatters demonstrated the effectiveness of WF-SCOSI toward non-invasive hemodynamic imaging applications.

Speed-enhanced scattering compensation method with sub-Nyquist sampling

A rapid feedback-based scattering compensation method is particularly important for guiding light precisely within turbid tissues, especially the dynamic tissues. However, the huge number of measurements that come from the underutilization of the signal frequency channel greatly limits the modulation speed. This paper introduces a rapid compensation method with the sub-Nyquist sampling which improves the channel utilization and the speed of wavefront shaping. The number of measurements is reduced to ∼1500 with 32 × 32 freedom, and the PBR of the focus reaches ∼200. The system performances are demonstrated by focusing the light through brain slices of different thicknesses.

Performance enhancement in wavefront shaping of multiply scattered light: a review

Significance

In nonballistic regime, optical scattering impedes high-resolution imaging through/inside complex media, such as milky liquid, fog, multimode fiber, and biological tissues, where confocal and multiphoton modalities fail. The significant tissue inhomogeneity-induced distortions need to be overcome and a technique referred as optical wavefront shaping (WFS), first proposed in 2007, has been becoming a promising solution, allowing for flexible and powerful light control. Understanding the principle and development of WFS may inspire exciting innovations for effective optical manipulation, imaging, stimulation, and therapy at depths in tissue or tissue-like complex media.

Aim

We aim to provide insights about what limits the WFS towards biomedical applications, and how recent efforts advance the performance of WFS among different trade-offs.

Approach

By differentiating the two implementation directions in the field, i.e., precompensation WFS and optical phase conjugation (OPC), improvement strategies are summarized and discussed.

Results

For biomedical applications, improving the speed of WFS is most essential in both directions, and a system-compatible wavefront modulator driven by fast apparatus is desired. In addition to that, algorithm efficiency and adaptability to perturbations/noise is of concern in precompensation WFS, while for OPC significant improvements rely heavily on integrating physical mechanisms and delicate system design for faster response and higher energy gain.

Conclusions

Substantial improvements in WFS implementations, from the aspects of physics, engineering, and computing, have inspired many novel and exciting optical applications that used to be optically inaccessible. It is envisioned that continuous efforts in the field can further advance WFS towards biomedical applications and guide our vision into deep biological tissues.

Wavefront shaping improves the transparency of the scattering media: a review

Significance

Wavefront shaping (WFS) can compensate for distortions by optimizing the wavefront of the input light or reversing the transmission matrix of the media. It is a promising field of research. A thorough understanding of principles and developments of WFS is important for optical research.

Aim

To provide insight into WFS for researchers who deal with scattering in biomedicine, imaging, and optical communication, our study summarizes the basic principles and methods of WFS and reviews recent progress.

Approach

The basic principles, methods of WFS, and the latest applications of WFS in focusing, imaging, and multimode fiber (MMF) endoscopy are described. The practical challenges and prospects of future development are also discussed.

Results

Data-driven learning-based methods are opening up new possibilities for WFS. High-resolution imaging through MMFs can support small-diameter endoscopy in the future.

Conclusion

The rapid development of WFS over the past decade has shown that the best solution is not to avoid scattering but to find ways to correct it or even use it. WFS with faster speed, more optical modes, and more modulation degrees of freedom will continue to drive exciting developments in various fields.

Introducing the Special Issue Honoring Lihong V. Wang, Pioneer in Biomedical Optics

The editorial concludes the JBO Special Issue Honoring Lihong V. Wang, outlining Prof. Wang's salient contributions to advancing the field of biomedical optics.

Single-mode regenerative amplification in multimode fiber

The peak power performance of ultrafast fiber lasers scales with fiber mode area, but large fibers host multiple modes that are difficult to control. We demonstrate a technique for single-mode operation of highly multimode fiber based on regenerative amplification. This results in a short-pulse fiber source with, to our knowledge, an unprecedented combination of features: high gain (>55 dB) with negligible amplified spontaneous emission, high pulse energy (>50 μJ), good beam quality (M2 ≤ 1.3), and transform-limited (300 fs) pulses from a single amplification stage. We discuss peak intensity scaling to much higher levels and other opportunities for short-pulse generation in regenerative fiber amplifiers.

Efficiently scanning a focus behind scattering media beyond memory effect by wavefront tilting and re-optimization

One of the main challenges in the wavefront shaping technique is to enable controllable light propagation through scattering media. However, the scanning of the focus generated by wavefront shaping is limited to a small range determined by the optical memory effect (ME). Here, we propose and demonstrate efficiently scanning a focus behind scattering media beyond the ME region using the wavefront tilting and re-optimization (WFT&RO) method. After scanning an initial focus to a desired position by wavefront tilting, our approach utilizes the scanned focus at a new position as the "guide star" to do wavefront re-optimization, which can not only enhance the intensity of the focus to the value before scanning but also accelerate the optimization speed. Repeat such a process, we can theoretically fast scan the focus to any position beyond the ME region while maintaining a relatively uniform intensity. We experimentally demonstrate the power of the method by scanning a focus with uniform intensity values through an optical diffuser within a range that is at least 5 folds larger than the ME region. Additionally, for the case of two cascaded optical diffusers, the scanning range achieved is at least 7 folds larger than the ME region. Our method holds promising implications for applications such as imaging through media, where the ability to control light through scattering media is crucial.

A Mathematical Model for Simulating Photoacoustic Signal Generation Process in Biological Tissues.. [DOI: 10.21203/rs.3.rs-2928563/v2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Background: Biomedical photoacoustic imaging (PAI) is a hybrid imaging modality based on the laser-generated ultrasound waves due to the photoacoustic (PA) effect physical phenomenon that has been reported firstly by A. G. Bell in 1880. Numerical modeling-based simulation for the PA signal generation process in biological tissues helps researchers for decreasing error trials in-vitro and hence decreasing error rates for in-vivo experiments. Numerical modeling methods help in obtaining a rapid modeling procedure comparable to pure mathematics. However, if a proper simplified mathematical model can be founded before applying numerical modeling techniques, it will be a great advantage for the overall numerical model. Most scientific theories, equations, and assumptions, been proposed to mathematically model the complete PA signal generation and propagation process in biological tissues, are so complicated. Hence, the researchers, especially the beginners, will find a hard difficulty to explore and obtain a proper simplified mathematical model describing the process. That’s why this paper is introduced. Methods: In this paper we have tried to simplify understanding for the biomedical PA wave’s generation and propagation process, deducing a simplified mathematical model for the whole process. The proposed deduced model is based on three steps: a- pulsed laser irradiance, b- diffusion of light through biological tissue, and c- acoustic pressure wave generation and propagation from the target tissue to the ultrasound transducer surface. COMSOL Multiphysics, which is founded due to the finite element method (FEM) numerical modeling principle, has been utilized to validate the proposed deduced mathematical model on a simulated biological tissue including a tumor inside. Results and Conclusion: The time-dependent study been applied by COMSOL has assured that the proposed deduced mathematical model may be considered as a simplified, easy, and fast startup base for scientific researchers to numerically model and simulate biomedical PA signals’ generation and propagation process utilizing any proper software like COMSOL.

A Mathematical Model for Simulating Photoacoustic Signal Generation Process in Biological Tissues.. [DOI: 10.21203/rs.3.rs-2928563/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Background Biomedical photoacoustic imaging (PAI) is a hybrid imaging modality based on the laser-generated ultrasound waves due to the photoacoustic (PA) effect physical phenomenon that has been reported firstly by A. G. Bell in 1880. Numerical modeling based simulation for PA signal generation process in biological tissues helps researchers for decreasing error trials in-vitro and hence decreasing error rates for in-vivo experiments. Numerical modeling methods help in obtaining a rapid modeling procedure comparable to pure mathematics. However, if a proper simplified mathematical model can be founded before applying numerical modeling techniques, it will be a great advantage for the overall numerical model. More scientific theories, equations, and assumptions through the biomedical PA imaging research literature have been proposed trying to mathematically model the complete PA signal generation and propagation process in biological tissues. However, most of them have so complicated details. Hence, the researchers, especially the beginners, will find a hard difficulty to explore and obtain a proper simplified mathematical model describing the process. That’s why this paper is introduced. Methods In this paper we have tried to simplify understanding for the biomedical PA wave’s generation and propagation process, deducing a simplified mathematical model for the whole process. The proposed deduced model is based on three steps: a- pulsed laser irradiance, b- diffusion of light through biological tissue, and c- acoustic pressure wave generation and propagation from the target tissue to the ultrasound transducer surface.