A Biophysically-Based Model of the Optical Properties of Skin Aging

This paper presents a time-varying, multi-layered biophysically-based model of the optical properties of human skin, suitable for simulating appearance changes due to aging. We have identified the key aspects that cause such changes, both in terms of the structure of skin and its chromophore concentrations, and rely on the extensive medical and optical tissue literature for accurate data. Our model can be expressed in terms of biophysical parameters, optical parameters commonly used in graphics and rendering (such as spectral absorption and scattering coefficients), or more intuitively with higher-level parameters such as age, gender, skin care or skin type. It can be used with any rendering algorithm that uses diffusion profiles, and it allows to automatically simulate different types of skin at different stages of aging, avoiding the need for artistic input or costly capture processes

3D Monte Carlo radiation transfer modelling of photodynamic therapy

We acknowledge the support of the UK Engineering and Physics Sciences Research Council (EPSRC) for funding through a studentship for C L Campbell as well as the Alfred Stewart Trust.The effects of ageing and skin type on Photodynamic Therapy (PDT) for different treatment methods have been theoretically investigated. A multilayered Monte Carlo Radiation Transfer model is presented where both daylight activated PDT and conventional PDT are compared. It was found that light penetrates deeper through older skin with a lighter complexion, which translates into a deeper effective treatment depth. The effect of ageing was found to be larger for darker skin types. The investigation further strengthens the usage of daylight as a potential light source for PDT where effective treatment depths of about 2 mm can be achieved.Publisher PD

An Introduction to Light Interaction with Human Skin

Despite the notable progress in physically-based rendering, there is still a long way to go before one can automatically generate predictable images of organic materials such as human skin. In this tutorial, the main physical and biological aspects involved in the processes of propagation and absorption of light by skin tissues are examined. These processes affect not only skin appearance, but also its health. For this reason, they have also been the object of study in biomedical research. The models of light interaction with human skin developed by the biomedical community are mainly aimed at the simulation of skin spectral properties which are used to determine the concentration and distribution of various substances. In computer graphics, the focus has been on the simulation of light scattering properties that affect skin appearance. Computer models used to simulate these spectral and scattering properties are described in this tutorial, and their strengths and limitations discussed. Keywords: natural phenomena, biologically and physically-based rendering

Appearance Modeling of Living Human Tissues

This is the peer reviewed version of the following article: Nunes, A.L.P., Maciel, A., Meyer, G.W., John, N.W., Baranoski, G.V.G., & Walter, M. (2019). Appearance Modeling of Living Human Tissues, Computer Graphics Forum, which has been published in final form at https://doi.org/10.1111/cgf.13604. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-ArchivingThe visual fidelity of realistic renderings in Computer Graphics depends fundamentally upon how we model the appearance of objects resulting from the interaction between light and matter reaching the eye. In this paper, we survey the research addressing appearance modeling of living human tissue. Among the many classes of natural materials already researched in Computer Graphics, living human tissues such as blood and skin have recently seen an increase in attention from graphics research. There is already an incipient but substantial body of literature on this topic, but we also lack a structured review as presented here. We introduce a classification for the approaches using the four types of human tissues as classifiers. We show a growing trend of solutions that use first principles from Physics and Biology as fundamental knowledge upon which the models are built. The organic quality of visual results provided by these Biophysical approaches is mainly determined by the optical properties of biophysical components interacting with light. Beyond just picture making, these models can be used in predictive simulations, with the potential for impact in many other areas

Modified lambert beer for bilirubin concentration and blood oxygen saturation prediction

Noninvasive measurement of health parameters such as blood oxygen saturation and bilirubin concentration predicted via an appropriate light reflectance model based on the measured optical signals is of eminent interest in biomedical research. This is to replace the use of conventional invasive blood sampling approach. This study aims to investigate the feasibility of using Modified Lambert Beer model (MLB) in the prediction of one’s bilirubin concentration and blood oxygen saturation value, SO2. This quantification technique is based on a priori knowledge of extinction coefficients of bilirubin and hemoglobin derivatives in the wavelength range of 440 – 500 nm. The validity of the prediction was evaluated using light reflectance data from TracePro raytracing software for a single-layered skin model with varying bilirubin concentration. The results revealed some promising trends in the estimated bilirubin concentration with mean ± standard deviation (SD) error of 0.255 ± 0.025 g/l. Meanwhile, a remarkable low mean ± SD error of 9.11 ± 2.48 % was found for the predicted SO2 value. It was concluded that these errors are likely due to the insufficiency of the MLB at describing changes in the light attenuation with the underlying light absorption processes. In addition, this study also suggested the use of a linear regression model deduced from this work for an improved prediction of the required health parameter values

BioSpec: A Biophysically-Based Spectral Model of Light Interaction with Human Skin

Despite the notable progress in physically-based rendering, there is still a long way to go before we can automatically generate predictable images of biological materials. In this thesis, we address an open problem in this area, namely the spectral simulation of light interaction with human skin, and propose a novel biophysically-based model that accounts for all components of light propagation in skin tissues, namely surface reflectance, subsurface reflectance and transmittance, and the biological mechanisms of light absorption by pigments in these tissues. The model is controlled by biologically meaningful parameters, and its formulation, based on standard Monte Carlo techniques, enables its straightforward incorporation into realistic image synthesis frameworks. Besides its biophysicallybased nature, the key difference between the proposed model and the existing skin models is its comprehensiveness, i. e. , it computes both spectral (reflectance and transmittance) and scattering (bidirectional surface-scattering distribution function) quantities for skin specimens. In order to assess the predictability of our simulations, we evaluate their accuracy by comparing results from the model with actual skin measured data. We also present computer generated images to illustrate the flexibility of the proposed model with respect to variations in the biological input data, and its applicability not only in the predictive image synthesis of different skin tones, but also in the spectral simulation of medical conditions

Improving snow albedo processes in WRF/SSiB regional climate model to assess impact of dust and black carbon in snow on surface energy balance and hydrology over western U.S.

Two important factors that control snow albedo are snow grain growth and presence of light‐absorbing impurities (aerosols) in snow. However, current regional climate models do not include such processes in a physically based manner in their land surface models. We improve snow albedo calculations in the Simplified Simple Biosphere (SSiB) land surface model coupled with the Weather Research and Forecasting (WRF) regional climate model (RCM), by incorporating the physically based SNow ICe And Radiative (SNICAR) scheme. SNICAR simulates snow albedo evolution due to snow aging and presence of aerosols in snow. The land surface model is further modified to account for deposition, movement, and removal by meltwater of such impurities in the snowpack. This paper presents model development technique, validation with in situ observations, and preliminary results from RCM simulations investigating the impact of such impurities in snow on surface energy and water budgets. By including snow‐aerosol interactions, the new land surface model is able to realistically simulate observed snow albedo, snow grain size, dust in snow, and surface water and energy balances in offline simulations for a location in western U.S. Preliminary results with the fully coupled RCM show that over western U.S., realistic aerosol deposition in snow induces a springtime average radiative forcing of 16 W/m2 due to a 6% albedo reduction, a regional surface warming of 0.84°C, and a snowpack reduction of 11 mm.Key PointsIncluding snow aging and aerosols in snow improves offline and WRF snow simulationsDust and black/organic carbon exerts nontrivial radiative forcing in western U.S.RCM simulation shows temperature increase and snow mass loss from aerosols in snowPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111782/1/jgrd52045.pd

In vivo measurement of skin microrelief using photometricstereo in the presence of interreflections

This paper proposes and describes an implementation of a novel photometric stereo based technique for in vivo assessment of three-dimensional (3D) skin topographyin the presence of interreflections. The proposed method illuminates skin with red, green, and blue colored lights and uses the resulting variation in surface gradients tomitigate the effects of interreflections. Experiments were carried out on Caucasian, Asian and African American subjects to demonstrate the accuracy of our methodand to validate the measurements produced by our system. Our method produced significant improvement in 3D surface reconstruction for all Caucasian, Asian and African American skin types. The results also illustrate the differences in recovered skin topography due to non-diffuse Bidirectional reflectance distribution function(BRDF) for each color illumination used, which also concur with the existing multispectral BRDF data available for skin