Peripheral cyanosis, the purple or blue coloration of hands and feet, can represent the initial signs of life-threatening medical conditions such as heart failure due to coronary occlusion. This makes its effective detection relevant for the timely screening of such conditions. In order to reduce the probability of false negatives during the assessment of peripheral cyanosis, one needs to consider that the manifestation of its characteristic chromatic attributes can be affected by a number of physiological factors, notably cutaneous pigmentation. The extent to which cutaneous pigmentation can impair this assessment has not been experimentally investigated to date, however. Although the detection of peripheral cyanosis in darkly-pigmented individuals has been deemed to be impractical, data to support or refute this assertion are lacking in the literature. In this paper, we address these issues through controlled in silico experiments that allow us to predictively reproduce appearance changes triggered by peripheral cyanosis (at different severity stages) on individuals with distinct levels of cutaneous pigmentation. Our findings indicate that the degree of detection difficulty posed by cutaneous pigmentation can be considerably mitigated by selecting the appropriate skin site to perform the observations.
The bluish appearance of veins located immediately beneath the skin has long been a topic of interest for biomedical optics researchers. Despite this interest, a thorough identification of the specific optical processes responsible for this phenomenon remains to be achieved. We employ controlled in silico experiments to address this enduring open problem. Our experiments, which are supported by measured data available in the scientific literature, are performed using first-principles models of light interaction with human skin and blood. Using this investigation approach, we quantitatively demonstrate that Rayleigh scattering caused by collagen fibrils present in the papillary dermis, a sublayer of the skin, can play a pivotal role in the bluish appearance of veins as suggested by previous works in this area. Moreover, also taking color perception aspects into account, we systematically assess the effects of variations in fibril radius and papillary dermis thickness on the coloration of veins under different illuminants. Notably, this assessment indicates that Rayleigh scattering elicited by reticulin fibrils, another type of fibril found in the papillary dermis, is unlikely to significantly contribute to the bluish appearance of veins. By strengthening the current understanding of light attenuation mechanisms affecting the appearance of skin and blood, our investigation contributes to the development of more effective technologies aimed at the noninvasive measurement of the physiological properties of these tissues.
Predictive light transport models based on first-principles simulation approaches have been proposed for complex organic materials. The driving force behind these efforts has been the high-fidelity reproduction of material appearance attributes without one having to rely on the manipulation of ad hoc parameters. These models, however, are usually considered excessively time consuming for rendering and visualization applications requiring interactive rates. In this paper, we propose a strategy to address this open problem with respect to one of the most challenging of these organic materials, namely the human iris. More specifically, starting with the configuration of a predictive iridal light transport model on a parallel-computing platform, we analyze the sensitivity of iridal appearance attributes to key model running parameters in order to achieve an optimal balance between fidelity and performance. We believe that the proposed strategy represents a step toward the real-time and predictive synthesis of high-fidelity iridal images for rendering and visualization applications, and it can be extended to other organic materials.
, "Detecting and monitoring water stress states in maize crops using spectral ratios obtained in the photosynthetic domain," J. Appl. Remote Sens. 11(3), 036025 (2017), doi: 10.1117/1.JRS.11.036025. Abstract. The reliable detection and monitoring of changes in the water status of crops composed of plants like maize, a highly adaptable C4 species in large demand for both food and biofuel production, are longstanding remote sensing goals. Existing procedures employed to achieve these goals rely predominantly on the spectral signatures of plant leaves in the infrared domain where the light absorption within the foliar tissues is dominated by water. It has been suggested that such procedures could be implemented using subsurface reflectance to transmittance ratios obtained in the visible (photosynthetic) domain with the assistance of polarization devices. However, the experiments leading to this proposition were performed on detached maize leaves, which were not influenced by the whole (living) plant's adaptation mechanisms to water stress. In this work, we employ predictive simulations of light-leaf interactions in the photosynthetic domain to demonstrate that the living specimens' physiological responses to dehydration stress should be taken into account in this context. Our findings also indicate that a reflectance to transmittance ratio obtained in the photosynthetic domain at a lower angle of incidence without the use of polarization devices may represent a cost-effective alternative for the assessment of water stress states in maize crops. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Measurement of the optical absorptance of blood can provide insight into its composition and behaviour. Accordingly, optical devices and sensors are commonly used in a clinical setting to measure the absorptance of blood, either directly or indirectly through measurement of skin spectral responses. These measurements enable the evaluation or constant monitoring of a patient's blood. In this paper, we perform predictive simulations to investigate the absorptance of blood and how it is affected by hemolysis. These simulations are performed using a cell-based light interaction model, known as CLBlood, which accounts for the orientation and distribution of red blood cells. This allows us to evaluate the effect of hemolysis under different flow conditions. Furthermore, we produce results in the ultraviolet, visible and infrared domains using CLBlood's hyperspectral capabilities. We then evaluate the sensitivity of the absorptance signature of blood to hemolysis in each of these domains under several experimental conditions. The observations in this paper enhance our understanding of the impact of hemolysis on the optical absorptance of blood, potentially leading to simplified and more accurate methods for its detection and monitoring.
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