Principal-component decomposition is applied to the analysis of noise for infrared images. It provides a set of eigenimages, the principal components, that represents spatial patterns associated with different types of noise. We provide a method to classify the principal components into processes that explain a given amount of the variance of the images under analysis. Each process can reconstruct the set of data, thus allowing a calculation of the weight of the given process in the total noise. The method is successfully applied to an actual set of infrared images. The extension of the method to images in the visible spectrum is possible and would provide similar results.

Applications using millimeter wave (mmW) and THz radiation have increased during the past few years. One of the principal applications of these technologies is the detection and identification of objects buried beneath the soil, in particular land mines and unexploded ordnances. A novel active mmW scanning imaging system was developed for this purpose. It is a hyperspectral system that collects images at different mmW frequencies from $90\text{\hspace{0.17em} to \hspace{0.17em}}140\text{\hspace{0.17em} GHz}$ using a vector network analyzer collecting backscattering mmW radiation from the buried sample. A multivariate statistical method, principal components analysis, is applied to extract useful information from these images. This method is applied to images of different objects and experimental conditions.

Purpose: This review explores mathematical models, blinking characterization, and non-invasive techniques to enhance understanding and refine clinical interventions for ocular conditions, particularly for contact lens wear. Methods: The review evaluates mathematical models in tear film dynamics and their limitations, discusses contact lens wear models, and highlights computational mechanical models. It also explores computational techniques, customization of models based on individual blinking dynamics, and non-invasive diagnostic tools like high-speed cameras and advanced imaging technologies. Results: Mathematical models provide insights into tear film dynamics but face challenges due to simplifications. Contact lens wear models reveal complex ocular physiology and design aspects, aiding in lens development. Computational mechanical models explore eye biomechanics, often integrating tear film dynamics into a Multiphysics framework. While different computational techniques have their advantages and disadvantages, non-invasive tools like OCT and thermal imaging play a crucial role in customizing these Multiphysics models, particularly for contact lens wearers. Conclusion: Recent advancements in mathematical modeling and non-invasive tools have revolutionized ocular health research, enabling personalized approaches. The review underscores the importance of interdisciplinary exploration in the Multiphysics approach involving tear film dynamics and biomechanics for contact lens wearers, promoting advancements in eye care and broader ocular health research.

This study presents a finite element analysis to model ocular biomechanics and the interactions between the human eye and contact lenses in the closed-eye condition. The closed-eye state, where the eyelids are fully shut, presents challenges for experimental measurements due to the invasive nature of accessing and analysing the contact lens and corneal interface, making simulation tools valuable for accurate characterisation. The primary objective of this study was to examine how CLs fold and twist and their impact on the cornea when the eye is closed. The secondary aim of this study was to assess how crucial contact lens parameters (Young’s modulus, base curve, and diameter) influence corneal stress distribution and the overall fit of the lens on the eye. The findings show that increasing Young’s modulus significantly reduces corneal stress and promotes uniform stress distribution, making it the most influential factor for wearer comfort and safety. While base curve and diameter variations primarily affect contact area, their impact on stress distribution is minimal. This research provides insights for improving contact lens design and enhancing safety for contact lens wearers.

The study of the interaction between light and biological tissue is of great help in the identification of diseases as well as structural alterations in tissues. In the present study, we have developed a tissue diagnostic technique by using multispectral imaging in the visible spectrum combined with principal component analysis (PCA). We used information from the propagation of light through paraffin-embedded tissues to assess differences in the eye tissues of control mouse embryos compared to mouse embryos whose mothers were deprived of folic acid (FA), a crucial vitamin necessary for the growth and development of the fetus. After acquiring the endmembers from the multispectral images, spectral unmixing was used to identify the abundances of those endmembers in each pixel. For each acquired image, the final analysis was performed by performing a pixel-by-pixel and wavelength-by-wavelength absorbance calculation. Non-negative least squares (NNLS) were used in this research. The abundance maps obtained for the first endmember revealed vascular alterations (vitreous and choroid) in the embryos with maternal FA deficiency. However, the abundance maps obtained for the third endmember showed alterations in the texture of some tissues such as the lens and retina. Results indicated that multispectral imaging applied to paraffin-embedded tissues enhanced tissue visualization. Using this method, first, it can be seen tissue damage location and then decide what kind of biological techniques to apply.