Search Results (5)

Imaging technologies based on vector optical fields hold significant potential in the biomedical field, particularly for non-invasive scattering imaging of anisotropic biological tissues. However, the dynamic and anisotropic nature of biological tissues poses severe challenges to the propagation and reconstruction of vector optical fields due to light scattering. To address this, we propose a deep learning-based polarization-resolved restoration method aimed at achieving the efficient and accurate imaging reconstruction from speckle patterns generated after passing through anisotropic and dynamic time-varying biological scattering media. By innovatively leveraging the two orthogonal polarization components of vector optical fields, our approach significantly enhances the robustness of imaging reconstruction in dynamic and anisotropic biological scattering media, benefiting from the additional information dimension of vectorial optical fields and the powerful learning capacity of a deep neural network. For the first time, a hybrid network model is designed that integrates convolutional neural networks (CNN) with a Transformer architecture for capturing local and global features of a speckle image, enabling adaptive vectorial restoration of dynamically time-varying speckle patterns. The experimental results demonstrate that the model exhibits excellent robustness and generalization capabilities in reconstructing the two orthogonal polarization components from dynamic speckle patterns behind anisotropic biological media. This study not only provides an efficient solution for scattering imaging of dynamic anisotropic biological tissues but also advances the application of vector optical fields in dynamic scattering environments through the integration of deep learning and optical technologies. Full article

Optical microscopy techniques are among the most used methods in biomedical sample characterization. In their more advanced realization, optical microscopes demonstrate resolution down to the nanometric scale. These methods rely on the use of fluorescent sample labeling in order to break the diffraction limit. However, fluorescent molecules’ phototoxicity or photobleaching is not always compatible with the investigated samples. To overcome this limitation, quantitative phase imaging techniques have been proposed. Among these, holographic imaging has demonstrated its ability to image living microscopic samples without staining. However, for a 3D assessment of samples, tomographic acquisitions are needed. Tomographic Diffraction Microscopy (TDM) combines holographic acquisitions with tomographic reconstructions. Relying on a 3D synthetic aperture process, TDM allows for 3D quantitative measurements of the complex refractive index of the investigated sample. Since its initial proposition by Emil Wolf in 1969, the concept of TDM has found a lot of applications and has become one of the hot topics in biomedical imaging. This review focuses on recent achievements in TDM development. Current trends and perspectives of the technique are also discussed. Full article

The modeling and processing of vectorial electromagnetic (EM) waves in inhomogeneous media are important problems in physics and engineering, and new methods need to be developed to incorporate novel vector sensor technology. Vectorial phenomena of EM waves in stratified atmospheric layers can be incorporated into governing equations by retaining the gradient of the refractive index when deriving the Maxwell Vector Wave Equation (MVWE) from Maxwell’s equations. The MVWE, as opposed to the scalar wave, Helmholtz, and paraxial equations, couples the EM field components in inhomogeneous media and thus captures important physics phenomena such as depolarization. Here, recent developments are reviewed on using sensor time series data to reconstruct electromagnetic waves that propagate through stratified media. In modern applications, often many sensors can be deployed simultaneously to observe electromagnetic waves. These networks of sensors can be used to improve the quality of the reconstructed EM wave fields and cross-validate the observed sensor time series. Lastly, the effects of noisy current densities on sensor time series are considered. Generally, as the sensor observes for longer periods of time, the variance of estimates of the wave field obtained from sensor time series data increases. As a result, longer sensor observation times do not always result in better estimates of the EM wave fields, and an optimal observation time can be obtained. Full article

This paper resists the virality of contemporary paranoia by turning to “French epistemology”, a philosophical ethos that embraces uncertainty and complexity by registering the transformative impact of scientific knowledge on thought. Despite its popular uses describing phenomena of communication today, the idea of virality comes from biomedicine. This paper, therefore, investigates the extent to which an epidemiological concept of viral transmission—the disease vector—can comprehend and encourage new possibilities of thought beyond paranoia. Briefly, I attempt to analyze thought as a vector. I pursue this by examining Delaporte’s important, but neglected, study of the 1832 Parisian cholera epidemic. First elucidating his reconstruction of the ways tentative epistemological progress intertwined with and supported projects of working-class and colonial control. My vectorial analysis then considers how his argument infects contemporary readers with doubts that undo the bases of paranoia. I pursue this analysis further via a methodological examination of Delaporte’s study as both carrier of predecessors’ methods and host in which they alter, becoming newly infectious. I conclude by reflecting on this formulation of thought as disease vector and what Delaporte’s singular treatment of the problem of error reveals about an ethos committed to registering the impact of knowledge on thought. Full article

The evaluation of the dynamics of accidents involving the overturning of farm tractors is difficult for both engineers and coroners. A clear reconstruction of the causes, vectorial forces, speed, acceleration, timing and direction of rear, front and side rollovers may be complicated by the complexity of the lesions, the absence of witnesses and the death of the operator, and sometimes also by multiple overturns. Careful analysis of the death scene, vehicle, traumatic lesions and their comparison with the mechanical structures of the vehicle and the morphology of the terrain, should help experts to reconstruct the dynamics of accidents and may help in the design of new preventive equipment and procedures. Full article