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Confocal Raman Microscopy with Adaptive Optics

Confocal Raman microscopy is a precise and label-free technique for analyzing thick samples at the microscale, but its use is often limited by weak Raman signals. Sample inhomogeneities introduce wavefront aberrations, further diminishing signal strength and requiring longer acquisition times. In this study, we present the first application of Adaptive Optics in confocal Raman microscopy to correct these aberrations, achieving substantial improvements in signal intensity and image quality. This approach integrates seamlessly with commercial microscopes without the need for hardware modifications. It utilizes a wavefront sensorless method, relying on an optofluidic, transmissive spatial light modulator attached to the microscope nosepiece to measure and correct aberrations. Experimental validation shows effective correction of aberrations in artificial scatterers and mouse brain tissue, enhancing spatial resolution and increasing signal intensity by up to 3.5 times. These results establ...
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TPEF: Improving speed and deep tissue imaging by holography (DASH and PMC)


DASH

The strong scattering process of photons in biological tissues is one main barrier for in vivo imaging of volumetric images. The current methods for avoiding scattering are adaptive optics, long wavelengths (infrared), and clearing the tissue. 

In adaptive optics, a converging algorithm adapts the beam shape in each new measurement. Dynamic adaptive scattering compensation holography (DASH) is a novel algorithm for enhancing the image quality for depth measurements down to 530 µm. The algorithm is iterative and finds the best converging point. Adaptive optics minimize the optical aberrations from scattering and optical systems. 

The next figure shows the deep imaging of microglia cells below a thickness of 500 µm of brain tissue (hippocampus). DASH uses interferometry for determining the most suitable phase for the measure. By this method is possible to image cells down to 500 µm.



Image is taken from M. May et al, "Fast holographic scattering compensation for deep tissue biological imaging", Nature communications, 2021. 

The phase topography is captured by using a wavefront sensor or digital holography. Further developments in machine learning may predict the best beam shape for measures. The next figure shows the optical setup of DASH, the spatial light modulator (SLM), scan galvos, and the 4f setups.



Image is taken from M. May et al, "Fast holographic scattering compensation for deep tissue biological imaging", Nature communications, 2021. 

DASH is a continuous algorithm. The method combines the holography method and standard phase pattern for correction. DASH converges faster than state-art-algorithms such as IMPAC and F-SHARP for deeper regions (500 µm) in the brain. 

Dynamic adaptive scattering compensation holography (DASH). Large SLM allows to correct multiple field points along the FOV. Distances larger than 500 µm. The enhancement factor is 10 times. 

Nonlinear imaging methods collect subcellular information. The main goal of adaptive optics is retrieving the phase and finding the best imaging optimization. 

The SLM splits the incident laser beam into a modulated wavefront Mn and corrected reference field Ci, n. Interferometry is then performed by varying the phase step. The enlarged image in the figure shows two beams, the blue one is the first corrected beam and the red beam enhances as the iteration increases. 

Image is taken from M. May et al, "Fast holographic scattering compensation for deep tissue biological imaging", Nature communications, 2021. 

The comparison between IMPACT and F-SHARP is displayed in the figure. IMPACT and DASH rely on the speed of the SLM. 



PMC

Novel correction scheme called parallel multi-point correction (PMC) in which Dynamic Adaptive Scattering compensation Holography (DASH) stands out. 

An incident beam is holographically split into a corrected field Ci,n (i, n are iteration and mode index) representing the current best wavefront correction and a test wavefront Mn, which represents the next mode for testing.

The phase pattern $/phi_{i,n,p}$ is:

$\Phi_{i,n,p}\;=\mathrm{angle}\left(\sqrt{{1-f}}\;\frac{C_{i,n}}{|C_{i,n}|}\,+\,\sqrt{{f}}\,e^{j}(M_{n}+\!\varphi_{p})\,\mathrm{\;\;}\right)$

$C_{i,n+1}= C_{i,n}~+\mathcal{A}_{i,n}~e^{j(M_{n}-\phi_{i,n})}$

The scalar value f determines the balance between the corrected and modulated wavefronts. The values of amplitude and 

$\Phi_{tot}\;=\mathrm{angle}\left(\sum_{l=1}^{L}\;e^{-((x-x_{l})^{2}+(y-y_{l})^{2})/(2w_{\mathrm{SIM}}^{2})}\ e^{j\mathrm{angle}(C_{l})}\;\nonumber\;\right)$

The width Wslm of the gaussian amplitude weighting can be freely chosen. 

PMC provides enhanced regions, which can be selected by the user.

Image is taken from M.A. May et al, "Simultaneous scattering compensation at multiple points in multi-photon microscopy", Biomedical Optics Express, 2021. 


Reference

M.A. May et al, "Fast holographic scattering compensation for deep tissue biological imaging", Nature communications, 2021.

M.A. May et al, "Simultaneous scattering compensation at multiple points in multi-photon microscopy", Biomedical Optics Express, 2021. 


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