Dynamic Speckle Research Articles

New Approaches to Determining the D/H Ratio in Aqueous Media Based on Diffuse Laser Light Scattering for Promising Application in Deuterium-Depleted Water Analysis in Antitumor Therapy

The development of affordable and reliable methods for quantitative determination of stable atomic nuclei in aqueous solutions and adjuvant agents used in tumor chemotherapy is an important task in modern pharmaceutical chemistry. This work quantified the deuterium/prothium isotope ratio in aqueous solutions through an original two-dimensional diffuse laser scattering (2D-DLS) software and hardware system based on chemometric processing of discrete interference patterns (dynamic speckle patterns). For this purpose, 10 mathematical descriptors (di), similar to QSAR descriptors, were used. Correlation analysis of bivariate “log di—D/H” plots shows an individual set of multi-descriptors for a given sample with a given D/H ratio (ppm). A diagnostic sign (DS) of differentiation was established: the samples were considered homeomorphic if 6 out of 10 descriptors differed by less than 15% (n ≥ 180). The analytical range (r = 0.987) between the upper (D/H ≤ 2 ppm) and lower (D/H = 180 ppm) limits for the quantification of stable hydrogen nuclei in water and aqueous solutions were established. Using the Spirotox method, a «safe zone» for protozoan survival was determined between 50 and 130 ppm D/H. Here, we discuss the dispersive (DLS, LALLS) and optical properties (refractive index, optical rotation angle) of the solutions with different D/H ratios that define the diffuse laser radiation due to surface density inhomogeneities. The obtained findings may pave the way for the future use of a portable, in situ diffuse laser light scattering instrument to determine deuterium in water and aqueous adjuvants.

Exploring temporal dynamics of ice melting through dynamic laser speckle imaging

Exploring temporal dynamics of ice melting through dynamic laser speckle imaging

Real-Time Observations of Leaf Vitality Extinction by Dynamic Speckle Imaging

Sap flow within a leaf is a critical indicator of plant vitality and health. This paper introduces an easy-to-use, non-invasive and real-time imaging method for sap microcirculation imaging. From the coherent backscattering of light on a leaf, we show that the acquisition frequency of dynamic speckle can be linked to the microcirculation speed inside the leaf. Unlike conventional methods based on speckle contrast, which use integration times long enough to observe temporal decorrelation within a single image, our approach operates in a regime where speckle patterns appear ‘frozen’ in each frame of a given sequence. This ‘frozen’ state implies that any decorrelation of the speckle pattern within a frame is negligible. However, between successive frames, decorrelation becomes substantial, and it is this inter-frame decorrelation that enables the extraction of dynamic information. In this context, the integration time primarily influences the radiometric levels, while the frame acquisition rate emerges as the key parameter for generating activity index maps. Thus, by accessing different ranges of sap flow activity levels by varying the frame acquisition rate, we reveal, in a non-invasive way, the anatomy of the leaf’s circulatory network with unprecedented richness. We experimentally validate the ability of the method to characterize the vitality of a fig leaf in real time by observing the continuous decrease in sap circulation, first in the smaller vessels and then in the larger ones, following the cutting of the leaf over a 48 h period.

Detection of hidden drawings using multi-wavelength dynamic speckle, tuneable algorithms, and unsupervised learning

Abstract We implemented an experiment to reveal hidden drawings on papyrus, utilizing an optical technique based on the speckle phenomenon. The goal is to optimize the detection of hidden objects. Our approach proposes using multiple wavelengths for illumination and tuneable algorithms to process the dynamic speckle images. By implementing the suggested method, we generated various results with varying quality, contingent upon the tuneable algorithm parameters. It is feasible to identify the optimal parameter combination to achieve the most effective visualization of the recovered image. To streamline the selection of tuneable algorithms and mitigate reliance on subjective visual judgment, we employed unsupervised machine learning techniques to determine the conditions necessary to achieve optimal results. This approach simplifies the selection procedure and offers an objective and non-invasive method. Furthermore, the proposed procedure holds promise for extending its application to uncover hidden paintings, subsurface archaeological artefacts, and other dynamic speckle experiments.

Characterization of Schiff base self-healing hydrogels by dynamic speckle pattern analysis

Self-healing hydrogels are emerging materials capable of restoring functionality after damage, making them highly suitable for biomedical applications, such as tissue engineering, wound healing, and drug delivery. In this study, we synthesize and characterize a novel biodegradable, conductive, and self-healing hydrogel. The synthesis is based on a Schiff base formed between gelatin and hyaluronic acid, and the dynamic reversible Schiff base bond provides the self-healing property. To characterize and assess the self-healing behavior of the hydrogel, dynamic speckle pattern (DSP) analysis is introduced as a non-destructive, non-contact, and easy-to-implement method. Speckle patterns are formed upon scattering of laser light from a diffusive matter and includes a huge overall information about the sample, to be extracted by statistical processing. DSP analysis is employed to monitor the self-healing process of the hydrogel at both macroscopic and microscopic scales. Experimental procedure involve in situ acquisition of speckle patterns over time under controlled environmental conditions, followed by statistical analysis to evaluate the internal dynamics of the healing process. Several statistical parameters are computed for real-time monitoring of the self-healing property of the hydrogel. The findings, on the one hand, underscore the potential of Schiff base hydrogels in advanced biomedical applications where self-healing properties are critical for sustained performance and longevity. On the other hand, the introduced analysis method shows its potential to serve as an effective approach for biomaterial characterization.

Using Dynamic Laser Speckle Imaging for Plant Breeding: A Case Study of Water Stress in Sunflowers.

This study focuses on the promising use of biospeckle technology to detect water stress in plants, a complex physiological mechanism. This involves monitoring the temporal activity of biospeckle pattern to study the occurrence of stress within the leaf. The effects of water stress in plants can involve physical and biochemical changes. Some of these changes may alter the optical scattering properties of leaves. The present study therefore proposes to test the potential of a biospeckle measurement to observe the temporal evolution in different varieties of sunflower plants under water stress. An experiment applying controlled water stress with osmotic shock using polyethylene glycol 6000 (PEG) was conducted on two sunflower varieties: one sensitive, and the other more tolerant to water stress. Temporal monitoring of biospeckle activity in these plants was performed using the average value of difference (AVD) indicator. Results indicate that AVD highlights the difference in biospeckle activity between day and night, with lower activity at night for both varieties. The addition of PEG entailed a gradual decrease in values throughout the experiment, particularly for the sensitive variety. The results obtained are consistent with the behaviour of the varieties submitted to water stress. Indeed, a few days after the introduction of PEG, a stronger decrease in AVD indicator values was observed for the sensitive variety than for the resistant variety. This study highlights the dynamics of biospeckle activity for different sunflower varieties undergoing water stress and can be considered as a promising phenotyping tool.

Tunable dynamical tissue phantom for laser speckle imaging.

We introduce a novel method to design and implement a tunable dynamical tissue phantom for laser speckle-based in-vivo blood flow imaging. This approach relies on stochastic differential equations (SDE) to control a piezoelectric actuator which, upon illuminated with a laser source, generates speckles of pre-defined probability density function and auto-correlation. The validation experiments show that the phantom can generate dynamic speckles that closely replicate both surfaces as well as deep tissue blood flow for a reasonably wide range and accuracy.

Method for measuring blood flow and depth of blood vessel based on laser speckle contrast imaging using 3D convolutional neural network: A preliminary study

Laser speckle contrast imaging (LSCI) is a technology that can acquire real-time two-dimensional perfusion images non-invasively. However, measuring perfusion velocity under a tissue is difficult due to its optical properties. Dynamic scattered light occurs by perfusion is diffused by the surrounding tissue and it depends on the depth of tissue. We aimed to develop a three-dimensional convolutional neural network (3D-CNN) model based on laser speckle contrast images to measure the flow velocity and the depth of tissue using a flow phantom. The training data was selected as a region containing both static speckles and dynamic speckles, and the model was trained on the laser speckle contrast image data. The trained model showed a measurement accuracy of more than 90 % for velocity and 99 % for depth measurement. This study has the potential of a deep-learning model based on LSCI to analyze the blood flow and depth of blood vessels in bio-applications.

Efficient non-line-of-sight tracking with computational neuromorphic imaging.

Non-line-of-sight (NLOS) sensing is an emerging technique that is capable of detecting objects hidden behind a wall, around corners, or behind other obstacles. However, NLOS tracking of moving objects is challenging due to signal redundancy and background interference. Here, we demonstrate computational neuromorphic imaging with an event camera for NLOS tracking, unaffected by the relay surface, which can efficiently obtain non-redundant information. We show how this sensor, which responds to changes in luminance within dynamic speckle fields, allows us to capture the most relevant events for direct motion estimation. The experimental results confirm that our method has superior performance in terms of efficiency, and accuracy, which greatly benefits from focusing on well-defined NLOS object tracking.

Dynamic speckle illumination wide-field fluorescence microscopy with actively optical manipulation of rotational angles.

We present a dynamic speckle illumination wide-field fluorescence microscopy (DSIWFM) combined with a line optical tweezers (LOTs) for rotational fluorescence sectioning imaging. In this method, large polystyrene fluorescent microspheres are stably trapped with LOTs, and precisely manipulated to rotate around a specific rotation axis. During the rotation process, multiple raw fluorescence images of trapped microspheres are obtained with dynamic speckle illumination. The root-mean-square (RMS) algorithm is used to extract the drastically changing fluorescent signals in the focal plane to obtain the fluorescence sectioning images of the samples at various angles. The influence of speckle granularity on the image quality of fluorescence sectioning images is experimentally analyzed. The rotational fluorescence sectioning images obtained by DSIWFM with LOTs could provide an alternative technique for applications of biomedical imaging.

Rolling shutter speckle plethysmography for quantitative cardiovascular monitoring.

We propose a new speckle-based plethysmography technique, termed rolling shutter speckle plethysmography (RSSPG), which can quantitatively measure the velocity and volume fluctuations of blood flow during the cardiac cycle. Our technique is based on the rolling shutter speckle imaging, where the short row-by-row time differences in the rolling shutter image sensors are used to measure the temporal decorrelation behavior of vertically elongated speckles from a single image capture. Temporal analysis of the speckle field provides rich information regarding the dynamics of the scattering media, such as both the dynamic scattering fraction and the speckle decorrelation time. Using a sequence of images, RSSPG can monitor fluctuations in the blood flow dynamics while separating velocity and volume changes in blood vessels and obtaining high-quality plethysmography waveforms compared to regular photoplethysmography. We demonstrate the quantitative RSSPG based on accurate fitting of the speckle dynamics model, as well as the qualitative RSSPG based on simple row-by-row correlation (RIC) calculation for fast and robust analysis. Based on exploratory in vivo experiment, we show that RSSPG can reliably measure pulsatile waveforms and heart rate variations in various conditions, potentially providing physiologically relevant information for cardiovascular monitoring.

Probing aptamer-mucin 1 binding events on polydopamine@carbon nanotubes modified cellulose paper interface using speckle pattern analysis for label free aptasensing

Herein, we have developed a cellulose paper-based aptasensing protocol by employing dynamic laser speckle (DLS) analysis for direct and label-free probing of the binding interface. Cellulose filter paper surface was modified by using the mussel adhesion chemistry of polydopamine modified carbon nanotubes (PDA@CNTS). The mussel chemistry resulted in strong adhesion and binding of PDA@CNTs on cellulose paper surface. The modified surface was subsequently employed in the construction of label free aptasensor for detection of cancer biomarker mucin 1 (MUC1). Taking advantage of DLS technique, it provided us with sensitive and accurate analysis of target biomarker MUC1 by the intrinsic randomness of patterns generated from cellulose based paper surface. The developed aptasensor was evaluated using DLS at various fabrication steps, where the scattered laser beams from these samples were collected and analyzed based on the obtained speckle patterns. Under the optimal experimental conditions, paper-based aptasensor achieved sensitive and selective detection of MUC1, exhibiting excellent linear range (15–100) µM with a limit of detection of 1 µM. This work presents a novel study of promising laser speckle paper-based aptasensor, providing new insights for the development of low-cost, sensitive, and portable paper-based analytical tools for biological applications.

Dynamic laser speckle study on the effect of TiO2 and SiO2 nanoparticles in coatings

The coatings of TiO2 and SiO2 nanoparticles mixed with latex paint on the sample are studied. The sample coin is coated primarily with latex paint alone and then with additives such as TiO2 and SiO2 nanoparticles separately with the same percentage of concentration. The sample is illumined by a coherent source of light and produces tiny bright and dark fingerprints by the interference effect of the scattered laser. This cigar-like granular pattern image is known as a speckle pattern which is recorded continuously during the drying process of paint. The modified properties due to the additives in paint on the coin are studied by speckle photography. The surface profile plotting method is adopted for the roughness analysis on the sample. Histogram and gray level co-occurrence matrix perform the intensity analysis in the paint. The brightness examine by means of bright/dark pixel counting method.

Polarization-driven dynamic laser speckle analysis for brain neoplasms differentiation

Polarization-driven dynamic laser speckle analysis for brain neoplasms differentiation

Optical improvement of the dynamic laser speckle for seed analysis using portable digital camera

Optical improvement of the dynamic laser speckle for seed analysis using portable digital camera

Biospeckle Laser On Clouds, a digital gateway aiming at collaborative research improvement

The Dynamic Laser Speckle (DLS) is a photonic phenomenon transformed into a technique to monitor tiny changes in many materials, particularly in biological ones (Biospeckle Laser – BSL). Its high sensitivity is key to monitor tiny changes in the tissues that can characterise biological features in medical and in agricultural samples. This work aimed to develop an environment at the world-wide-web to share raw data of BSL and to offer access to an interactively online analysis with tutorials. The gateway designed was implemented using PHP and JavaScript tools solving the challenges of managing data (images) and online interactive use. The result was an easy-to-use environment boosting the BSL research. The early results presented thousands of accesses and of more than one hundred different users from all around the world.

SPECKLE IMAGES OF THE VESSELS AND HYDRODYNAMIC PHANTOMS IN OPTICAL COHERENCE TOMOGRAPHY

The results of a study of a series of sequential images of a vessel and a hydrodynamic phantom of biological tissues obtained using a Spectral Domain Optical Coherence Tomography (SP OCT) are presented. Acquired data were processed and histograms of speckle distributions were created. They demonstrated differences in the intensity distribution for three different areas of the OCT image: (1) free space, (2) wall of the vessel, and (3) the flow of scatterers. Using an optimization algorithm the histograms were approximated by various distribution functions, best result was demonstrated by the beta distribution with the determination coefficient R2 ~ 0.95. The resulting distributions quantitatively demonstrate effect of tissue heterogeneity. They show significant differences in the values of the shape and scale parameters, corresponding to the obtained beta distribution parameters, which were α ~ 1.7, β ~ 20.5 for free space, α ~ 3.1, β ~ 5.5 for the wall region of the phantom, α ~ 2.6, β ~ 1.7 for the flow of the scattering liquid. Variance matrices of the OCT images, which show correlation of speckles between adjacent pixels and those of the successive images were also obtained. Brighter areas of the variance matrix indicate a dynamic speckle structure in OCT images, while low brightness of the areas indicates static speckle structure, on the contrary.

Contactless estimation of apple fruit respiration rate using machine learning models based on laser speckle imaging

This article presents the application of the laser speckle imaging method, a nondestructive and contactless method monitoring the gas exchange rate of intact apples. Red and infrared lasers in a typical setup for laser speckle imaging were used. A new parameter, speckle pattern relaxation time, has been proposed to evaluate speckle dynamics. Machine learning methods were used to develop a set of predictive models calibrated and validated against the respiration rate of two apple fruit cultivars measured with the flush system. The model with the highest performance used three variables: the speckle pattern relaxation time (τRED or τIR), fruit mass, and categorical variables describing apple varieties. This model provided satisfactorily low values of mean absolute prediction errors of 6.04%. Data from laser light scattering measurements combined with modern machine learning algorithms provided a nondestructive and fast method for estimating the apple fruit respiration rate. The developed solution has the potential for a wide range of industrial applications, especially in fruit storage, where the fruit respiration rate indicates optimal storage conditions.

The liquid-to-solid transition of FUS is promoted by the condensate surface

A wide range of macromolecules can undergo phase separation, forming biomolecular condensates in living cells. These membraneless organelles are typically highly dynamic, formed reversibly, and carry out essential functions in biological systems. Crucially, however, a further liquid-to-solid transition of the condensates can lead to irreversible pathological aggregation and cellular dysfunction associated with the onset and development of neurodegenerative diseases. Despite the importance of this liquid-to-solid transition of proteins, the mechanism by which it is initiated in normally functional condensates is unknown. Here we show, by measuring the changes in structure, dynamics, and mechanics in time and space, that single-component FUS condensates do not uniformly convert to a solid gel, but rather that liquid and gel phases coexist simultaneously within the same condensate, resulting in highly inhomogeneous structures. Furthermore, our results show that this transition originates at the interface between the condensate and the dilute continuous phase, and once initiated, the gelation process propagates toward the center of the condensate. To probe such spatially inhomogeneous rheology during condensate aging, we use a combination of established micropipette aspiration experiments together with two optical techniques, spatial dynamic mapping and reflective confocal dynamic speckle microscopy. These results reveal the importance of the spatiotemporal dimension of the liquid-to-solid transition and highlight the interface of biomolecular condensates as a critical element in driving pathological protein aggregation.

Assessment of adulteration in honey by artificial sweeteners using dynamic laser speckle technique

Our research work uses the dynamic laser speckle technique for the first time to analyze the adulteration of “Dabur Honey” with two golden syrups Dhampur Green Golden Syrup (DGGS) and Solar Golden Syrup (SGS) as adulterate. Identifying 25% adulteration in honey by sweeteners is challenging due to several reasons, such as the complexity of honey composition and the similarity of some sweeteners to honey. A spatially filtered He-Ne laser beam is made to pass through adulterated samples. Forwarding scattered light is captured using a charge-coupled device (CCD) camera and Digital Image Processing is used to analyze the images. Seven textures and six features of images are evaluated. For 20% adulteration in honey by both the adulterates, a significant percentage change of 17%, 16%, 16%, 13%, and 11% is observed in Angular Second Moment, Covariance, Autocorrelation, Inertia, and Kurtosis respectively. Additionally, for a 20% adulteration in honey by DGGS and SGS separately, a notable percentage change of 3.8% and 6.6% respectively in the value of Inertia Moment (IM) is obtained. Thus, it is concluded that the above image processing algorithms can be used to detect 20% adulteration in pure honey.