In this presentation we show a method capable of measuring and correcting field dependent aberration in a microscope setup without a dedicated wavefront sensor using a pupil conjugated deformable lenses in combination with anisoplanatic deconvolution.
We present a microscopy method capable of measuring aberrations in all the poits of the field of view and to correct for the field-dependent aberrations in a closed loop multi conjugated AO system using two deformable lenses and no wavefront sensor.
Tomographic inspection of fluorescent labels distributed within a specimen is an important aspect in biology. Light sheet fluorescent microscopy (LSFM) offers a powerful and simple tool to selectively slice the sample and let us directly obtain a tomographic view of the specimen. However, due to non-isotropic resolution of the technique along the axial scanning, one may want to combine different views of the object and add deconvolution to the process in order to achieve higher resolution. Typically, multi-view Bayesian methods based on Richardson-Lucy deconvolution are used for this task once the datasets are exactly registered against each other. In this work, instead, we begin to investigate how to avoid the alignment procedure and use a direct algorithm to form a multi-view tomographic reconstruction. To do this, we developed a new framework based on auto-correlation analysis that let us achieve deconvolved reconstructions starting from blurred auto-correlations. Since the latter are insensitive to shifts, we can combine the auto-correlations coming from multi-view acquisitions without taking care of the registration procedure.
The reconstruction of an object hidden behind a scattering curtain is a modern topic in the field of imaging, which has stimulated an active scientific production over the past few years. However, most of the work done in the field was in addressing the reconstruction of a bi-dimensional object. Here, instead, we tackle the reconstruction of a three-dimensional fluorescent sample hidden behind an opaque layer. To do so, we show that the auto-correlation operation well behave in projection tomography, letting us to reconstruct a three-dimensional auto-correlation of the object. By having access to such information, it is possible to implement a phase retrieval algorithm to roll back to the actual reconstruction of the specimen.
Time-domain diffuse optics exploits near infrared light pulses diffused in turbid samples to retrieve their optical properties e.g., absorption and reduced scattering coefficients. Typically, interference effect are discarded, but speckle effects are exploited in other techniques e.g., diffuse correlation spectroscopy (DCS) to retrieve information regarding the tissue dynamics. Here, using a highly coherent Ti:Sapphire mode-locked laser and a single-mode detection fiber, we report the direct observation of temporal fluctuations in the measured distribution of time-of-flights (DTOF) curve. We study the dependence of these fluctuations on the sample dynamical properties (moving from fluid to rigid tissue-mimicking phantoms) and on the area of the detection fiber, which is directly linked to the number of collected coherence areas. Our observation agree with a time-resolved speckle pattern, and may enable the simultaneous monitoring of the tissue optical and dynamical properties.
Optical Projection Tomography (OPT) techniques are limited by the nature of light interaction with tissues. Some of these limitations arise from the scattering phenomena or the weak transparency of the samples, restricting the depth of penetration and the differentiation of structures due to image blurriness. Recent advances in detection technologies enable the use of new promising light spectrum imaging windows such as the Near-Infrared (NIR) II-a, which comprises wavelengths within the range between 1300 to 1400 nm. Light in this frequency band has interesting properties that could increase the depth of penetration, reduce the auto fluorescence and the scattering.
In this work we aim to explore the possibilities of this wavelengths and compare them with imaging in shorter wavelengths. At first, we have examined its optical properties in detail, finding which band of the spectrum works best for tissue imaging. Afterwards we built an OPT setup using two lasers with wavelengths from different windows to analyze the benefits of the IIa near infrared experimentally. Finally, we discuss the results and we propose ways to exploit all the advantages that the use of these wavelengths can bring into the state-of-the-art optical imaging techniques.
Optical tomography in biomedical imaging is a highly dynamic field in which non-invasive optical and computational techniques are combined to obtain a three dimensional representation of the specimen we are interested to image. Although at optical wavelengths scattering is the main obstacle to reach diffraction limited resolution, recently several studies have shown the possibility to image even objects fully hidden behind a turbid layer exploiting the information contained in the speckle autocorrelation via an iterative phase retrieval algorithm. In this work we explore the possibility of blind three dimensional reconstruction approach based on the Optical Projection Tomography principles, a widely used tool to image almost transparent model organism such as C. Elegans and D. Rerio. By using autocorrelation information rather than projections at each angle we prove, both numerically and experimentally, the possibility to perform exact three dimensional reconstructions via a specifically designed phase retrieval algorithm, extending the capability of the projection-based tomographic methods to image behind scattering curtains. The reconstruction scheme we propose is simple to implement, does not require post-processing data alignment and moreover can be trivially implemented in parallel to fully exploit the computing power offered by modern GPUs, further reducing the need for costly computational resources.
Optical Neuroimaging is a highly dynamical field of research owing to the combination of many advanced imaging techniques and computational tools that uncovered unexplored paths through the functioning of the brain. Light propagation modelling through such complicated structures has always played a crucial role as the basis for a high resolution and quantitative imaging where even the slightest improvement could lead to significant results. Fluorescence Diffuse Optical Tomography (fDOT), a widely used technique for three dimensional imaging of small animals and tissues, has been proved to be inaccurate for neuroimaging the mouse head without the knowledge of a-priori anatomical information of the subject. Commonly a normalized Born approximation model is used in fDOT reconstruction based on forward photon propagation using Diffusive Equation (DE) which has strong limitations in the optically clear regime. The presence of the Cerebral Spinal Fluid (CSF) instead, a thin optically clear layer surrounding the brain, can be more accurately taken into account using Monte Carlo approaches which nowadays is becoming more usable thanks to parallelized GPU algorithms. In this work we discuss the results of a synthetic experimental comparison, resulting to the increase of the accuracy for the Born approximation by introducing the CSF layer in a realistic mouse head structure with respect to the current model. We point out the importance of such clear layer for complex geometrical models, while for simple slab phantoms neglecting it does not introduce a significant error.
The combined use of a wavefront modulator and a scattering medium forms an "opaque lens" which forces the light to focus tightly. The adaptive focus has the same shape as the correlation function of the original speckle pattern and it can be generated at defined positions with resolution up to hundreds of nanometers. We have demonstrated that manipulating the speckle pattern spatial components can structure the shape of the focus. Exploiting selectively spatial-frequencies from the speckle components we realized opaque lenses able to produce sub-correlation foci and Bessel beams.
Recently great progress has been made in biological and biomedical imaging by combining non-invasive optical methods, novel adaptive light manipulation and computational techniques for intensity-based phase recovery and three dimensional image reconstruction. In particular and in relation to the work presented here, Optical Projection Tomography (OPT) is a well-established technique for imaging mostly transparent absorbing biological models such as C. Elegans and Danio Rerio. On the contrary, scattering layers like the cocoon surrounding the Drosophila during the pupae stage constitutes a challenge for three dimensional imaging through such a complex structure. However, recent studies enabled image reconstruction through scattering curtains up to few transport mean free paths via phase retrieval iterative algorithms allowing to uncover objects hidden behind complex layers. By combining these two techniques we explore the possibility to perform a three dimensional image reconstruction of fluorescent objects embedded between scattering layers without compromising its structural integrity. Dynamical cross correlation registration was implemented for the registration process due to translational and flipping ambiguity of the phase retrieval problem, in order to provide the correct aligned set of data to perform the back-projection reconstruction. We have thus managed to reconstruct a hidden complex object between static scattering curtains and compared with the effective reconstruction to fully understand the process before the in-vivo biological implementation.
By compensating the random phase delay acquired while a light beam crosses a scattering curtain, it is possible to address the light at selected target position beyond the obstacle. An opaque lens can produce foci with a resolution higher than conventional optics if a strongly scattering medium is exploited. In practice, subwavelength resolution is obtained only for weakly transmitting samples. Herein we present a method which allows obtaining tiny bright optical spots even in presence of a minimum amount of scattering (semi-transparent media) in the beam path. Using a High-Pass spatial filter we block the pseudo-ballistic components of the transmitted beam, we are able to gather light on a spot with a diameter which is one third of the typical speckle grain in absence of the filter.
One of the major challenges within Optical Imaging, photon propagation through clear layers embedded between scattering tissues, can be now efficiently modelled in real-time thanks to the Monte Carlo approach based on GPU. Because of its nature, the photon propagation problem can be very easily parallelized and ran on low cost hardware, avoiding the need for expensive Super Computers. A comparison between Diffusion and MC photon propagation theory is presented in this work with application to neuroimaging, investigating low scattering regions in a mouse-like phantom. Regions such as the Cerebral Spinal Fluid, are currently not taken into account in the classical computational models because of the impossibility to accurately simulate light propagation using fast Diffusive Equation approaches, leading to inaccuracies during the reconstruction process. The goal of the study presented here, is to reduce and further improve the computation accuracy of the reconstructed solution in a highly realistic scenario in the case of neuroimaging in preclinical mouse models.
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