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

Standardizing the classification of skin tears: validity and reliability testing of the International Skin Tear Advisory Panel Classification System in 44 countries

Background: Skin tears are acute wounds that are frequently misdiagnosed and under‐reported. A standardized and globally adopted skin tear classification system with supporting evidence for diagnostic validity and reliability is required to allow assessment and reporting in a consistent way. Objectives:To measure the validity and reliability of the International Skin Tear Advisory Panel (ISTAP) Classification System internationally. Methods: A multicountry study was set up to validate the content of the ISTAP Classification System through expert consultation in a two‐round Delphi procedure involving 17 experts from 11 countries. An online survey including 24 skin tear photographs was conducted in a convenience sample of 1601 healthcare professionals from 44 countries to measure diagnostic accuracy, agreement, inter‐rater reliability and intrarater reliability of the instrument. Results:A definition for the concept of a ‘skin flap’ in the area of skin tears was developed and added to the initial ISTAP Classification System consisting of three skin tear types. The overall agreement with the reference standard was 0·79 [95% confidence interval (CI) 0·79–0·80] and sensitivity ranged from 0·74 (95% CI 0·73–0·75) to 0·88 (95% CI 0·87–0·88). The inter‐rater reliability was 0·57 (95% CI 0·57–0·57). The Cohen's Kappa measuring intrarater reliability was 0·74 (95% CI 0·73–0·75). Conclusions: The ISTAP Classification System is supported by evidence for validity and reliability. The ISTAP Classification System should be used for systematic assessment and reporting of skin tears in clinical practice and research globally.info:eu-repo/semantics/publishedVersio

Optical investigation of three‐dimensional human skin equivalents: A pilot study

Human skin equivalents (HSEs) are three-dimensional living models of human skin that are prepared in vitro by seeding cells onto an appropriate scaffold. They recreate the structure and biological behaviour of real skin, allowing the investigation of processes such as keratinocyte differentiation and interactions between the dermal and epidermal layers. However, for wider applications, their optical and mechanical properties should also replicate those of real skin. We therefore conducted a pilot study to investigate the optical properties of HSEs. We compared Monte Carlo simulations of (a) real human skin and (b) two-layer optical models of HSEs with (c) experimental measurements of transmittance through HSE samples. The skin layers were described using a hybrid collection of optical attenuation coefficients. A linear relationship was observed between the simulations and experiments. For samples thinner than 0.5 mm, an exponential increase in detected power was observed due to fewer instances of absorption and scattering

Recurrent somatic mutations in POLR2A define a distinct subset of meningiomas

RNA polymerase II mediates the transcription of all protein-coding genes in eukaryotic cells, a process that is fundamental to life. Genomic mutations altering this enzyme have not previously been linked to any pathology in humans, which is a testament to its indispensable role in cell biology. On the basis of a combination of next-generation genomic analyses of 775 meningiomas, we report that recurrent somatic p.Gln403Lys or p.Leu438_His439del mutations in POLR2A, which encodes the catalytic subunit of RNA polymerase II (ref. 1), hijack this essential enzyme and drive neoplasia. POLR2A mutant tumors show dysregulation of key meningeal identity genes including WNT6 and ZIC1/ZIC4. In addition to mutations in POLR2A, NF2, SMARCB1, TRAF7, KLF4, AKT1, PIK3CA, and SMO4 we also report somatic mutations in AKT3, PIK3R1, PRKAR1A, and SUFU in meningiomas. Our results identify a role for essential transcriptional machinery in driving tumorigenesis and define mutually exclusive meningioma subgroups with distinct clinical and pathological features

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

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given

On the predictive modeling of visible light interaction with fresh and environmentally stressed monocotyledonous leaves.

ABSTRACT The author has recently proposed a model to simulate light interactions with monocotyledonous (unifacial) leaves in the infrared domain. In this paper, we evaluate the applicability of this model to simulations performed in the visible (photosynthetic) domain, and aimed at the investigation of biophysical responses triggered by nutrient and water stress. The model's fidelity and predictability in this spectral domain are assessed through quantitative and qualitative comparisons of modeled results with measured data obtained for maize specimens. Its predictive capabilities are further demonstrated through the simulation of reflectance profiles resulting from experiments involving maize leaves under different water reduction procedures

Modeling the interaction of infrared radiation (750–2500nm) with bifacial and unifacial plant leaves. Remote Sensing of Environment 100

Abstract Plants are arguably among the most investigated remote sensing targets. Due to their economical and environmental importance, several models to simulate radiation transport and absorption by foliar tissues have been proposed in remote sensing and related fields. The main goal of this research is to present alternative modeling strategies for the investigation of these phenomena. These solutions consist in algorithmic models specifically designed to simulate the interaction of radiation with bifacial and unifacial plant leaves. Their flexible formulations based on standard Monte Carlo techniques make their implementation straightforward and allow their use in investigations involving different regions of the electromagnetic spectrum of radiation. In this paper, they are examined in the context of infrared applications. This choice is motivated by the simulation challenges posed by the processes that relate biophysical characteristics to optical properties of plant leaves in this domain. The accuracy and predictability of the proposed models have been evaluated through comparisons between modeled results and measured data. The results of these evaluations illustrate the applicability of the proposed models to investigations involving the predictive simulation of foliar spectral signatures.