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This chapter reviews the advances in light control through complex media using a DMD. Although these devices are known for their amplitude modulation capabilities, the implementation of binary holographic techniques effectively converts them into phase modulation devices. The fast decorrelation time of tissue, in the milliseconds time scale, motivates the research and development of fast focusing and imaging methods. The main advantage of using these MEMS devices, is the high switching speed, up to more than 20 kHz, improving the bandwidth with respect to the widely used LC-SLMs. DMDs have allowed reducing the total focusing time through complex media to tens of milliseconds, close to the speckle decorrelation times of dynamic biological media (tissue). The signal-to-noise ratio (SNR) of the signal detected is critical in this type of high-speed experiment because SNR decreases with the integration time. Therefore, the implementation of algorithms designed for low SNR environments will be required in the future.
In this chapter, we describe the use of a MEMS device to enhance microscopic focusing in scattering media. We begin the chapter with the manufacturing and actuation mechanism of MEMS SLMs. Then we illustrate how focusing through scattering media is achieved using both monochromatic and chromatic light. In recent development, two- and three-photon microscopy is demonstrated with MEMS SLMs for scattered light control. Lastly, conjugate AO is provided as future direction to the readers to overcome field of view limitations most for subsurface imaging applications.
In this chapter, we introduce and review recent research works based on the coupling optical wavefront shaping and photoacoustics. Coupling these two research fields, that have until recently developed rather independently, offers mutual advantages for both fields: on the one hand, the photocoustic effect provides a powerful sensing mechanism for optical wavefront shaping techniques, while on the other hand photoacoustic imaging can greatly benefit from optical wavefront shaping techniques. This chapter first introduces the principle of photoacoustics relevant in the context of this chapter, including an introduction to the photoacoustic effect and a brief overview of the principles of biomedical photoacoustic imaging. We then first review the recent works on photoacoustic-guided optical wavefront shaping, either with optimization or transmission-matrix approaches, and finally illustrate how optical wavefront shaping can be applied to develop minimally invasive photoacoustic microendscopy mith multimode fibers. Some parts of this chapter have been adapted from a recent review article on coupling photoacoustics and coherent light [1].
We review adaptive optics (AO) in biological imaging using direct wavefront measurement. Here light from a point source in the specimen is used to measure the wavefront with a detector such as a Shack-Hartmann wavefront sensor, similar to the approach that is used in astronomy. The benefit of direct wavefront measurement relative to the sensorless methods is that the wavefront can be measured quickly in one step. Typically sensorless methods are iterative, requiring a number of measurements. Taking multiple measurements can take more time and may expose the sample to more light which can lead to photo-bleaching. Another benefit is that some indirect methods use optimization of a merit function such as image sharpness or image intensity. In direct wavefront sensing the wavefront aberration is directly measured and corrected rather than optimized. As we shall discuss, a common metric for direct wavefront measurement and correction is the Strehl ratio which is defined as the ratio of the on-axis beam intensity to the diffraction limited beam intensity. The objective is getting as close as possible to the diffraction limit.
In addition to the many hardware methods for wavefront shaping described in the previous chapters, it is also possible to modify the wavefront computationally. Using interferometric detection, the complex optical wavefront can be measured. The phase of the wavefront can then be adjusted in software in a method analogous to that of a deformable mirror. This method is termed digital adaptive optics or computational adaptive optics (CAO). This is distinct from a previously published method of the same name which used ray tracing to guide amplitude deconvolution of 3-D datasets.
As the signal in multiphoton microscopy inherently has nonlinear dependence on light intensity (e.g. second order nonlinearity in two-photon excitation, third order nonlinearity in three-photon excitation), the combination of nonlinearity and iterative feedback is expected to work well in practice. We named this method Iterative Multi-Photon Adaptive Compensation Technique (IMPACT).
Often, optical scattering is not quite as random as the transmission matrix implies. One might not have to measure all of its values for a complete picture of light’s input-output behavior. We examin three examples of non-randomness: the optical memory effect, the translation memory effect, and sparsity introduced within a four dimensional ray space.
In this Chapter, we introduce several methods capable of focusing light deep inside scattering media noninvasively, without invasively implanting guide stars. The first method—time-reversed ultrasonically encoded (TRUE) light focusing—uses focused ultrasound as the guide star, and selectively phase-conjugates light whose frequency is acousto-optically shifted. The focal spot size is acoustic-diffraction-limited, and can be further reduced. The second method—time-reversed adapted perturbation (TRAP) light focusing—detects perturbation in the scattered light due to dynamic objects, and focuses by subsequent OPC. This method can reach optical-diffraction-limited focus because the focus tracks the dynamic object. The third method—ultrasonically encoded wavefront shaping (SEWS)—uses focused ultrasound as a guide star, which tags light via the acousto-optic effect as WFS feedback to reach an acoustic-diffraction-limited focal spot size. The last method— photoacoustically guided wavefront shaping (PAWS)—employs nonlinear photoacoustic signals as the feedback for WFS to achieve optical-diffraction-limited focusing .
Learn about the theory, techniques and applications of wavefront shaping in biomedical imaging using this unique text. With authoritative contributions from researchers who are defining the field, cutting-edge theory is combined with real-world practical examples, experimental data and the latest research trends to provide the first book-level treatment of the subject. It is suitable for both background reading and use in a course, with coverage of essential topics such as adaptive optical microscopy, deep tissue microscopy, time reversal and optical phase conjugation, and tomography. The latest images from the forefront of biomedical imaging are included, and full-colour versions are available in the eBook version. Researchers, practitioners and graduate students in optics, biophotonics, biomedical engineering, and biology who use biomedical imaging tools and are looking to advance their knowledge of the subject will find this an indispensable resource.