Texture‐based characterization of subskin features by specified laser speckle effects at λ = 650 nm region for more accurate parametric ‘skin age’ modelling

Abstract

Objective: The textural structure of "skin age" related sub-skin components enables us to identify and analyse their unique characteristics, thus making substantial progress towards establishing an accurate skin age model. Methods: This is achieved by a two stage process. First by the application of textural analysis using laser speckle imaging, which is sensitive to textural effects within the λ=650 nm spectral band region. In the second stage a Bayesian inference method is used to select attributes from which a predictive model is built. Results: This technique enables us to contrast different skin age models, such as the laser-speckle effect against the more widely used normal light (LED) imaging method, whereby it is shown that our laser speckle based technique yields better results. Conclusion: The method introduced here is non-invasive, low-cost and capable of operating in real-time; having the potential to compete against high-cost instrumentation such as confocal microscopy or similar imaging devices used for skin age identification purposes.

Scanning of skin gloss by a diffractive optical element-based handheld glossmeter

“…On the contrary, at BH, IS demonstrated higher average gloss value than LS, which was also higher than that of DS. The lower LS gloss value at BH, among other factors, could be largely due to the dryness [1] of the skin evident in Fig. 2a.…”

“…The illumination of the surface is at 6° angle of light incidence. Due to the scattering of the laser beam from skin structure, in the far-field region appears a wavefront that presents laser speckle pattern [1]. The role of the DOE is to act as a wavefront sensor that spatially filters the specular reflection, reducing the noise from the speckle pattern [9], from an object (reconstruction of the computer-generated hologram by a scattered wave) to pass onto a single-cell photodiode, which captures the intensity.…”

“…Low-cost, simple and easy-to-use optical devices in the assessment of skin properties have become important in healthcare and the cosmetic industry. The optical properties of skin are influenced by the color, age, texture [1], the refractive index [2,3], and the anisotropic nature of the sub-skin layer. Conventional devices for the measurement of skin parameters, e.g., aging involve the use of confocal microscopy [4], among others, which are comprehensive but expensive for the persons who readily need them.…”

“…It has also been demonstrated that lowlevel laser source in the visible or near infrared region presents better light-tissue interactions, especially, in the biological medium than LEDs. Optimal wavelengths that have been suggested for skin characterisation and laser therapy are 635 and 650 nm [1,11,12].…”

Progressive Observation of Covid-19 Vaccination Effects on Skin-Cellular Structures by Use of Intelligent Laser Speckle Classification (ILSC) Technique

“…In the current literature, there is only one study [15] which unifies laser speckle contrast imaging with artificial intelligence (neural networks) but differs from our proposed work in terms of its application and outputs. Here, ILSC is an integrated technique [9,16,22] which is comprised of different disciplinary methods, providing high sensitivity and discrimination power to detect subtle differences even at the sub-cellular level. The method detects laser speckles' textural differences, not for only a single cell unit but rather on the whole cellular network, to detect any common property or structural changes in all cells simultaneously, since all cells are naturally identical to each other or react to external effects in the same way.…”