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两层介质的空间域光谱学。

Spatial frequency domain spectroscopy of two layer media.

机构信息

University of California, Irvine, Beckman Laser Institute, Laser Microbeam and Medical Program, 1002 Health Sciences Road, Irvine, California 92612, USA.

出版信息

J Biomed Opt. 2011 Oct;16(10):107005. doi: 10.1117/1.3640814.

Abstract

Monitoring of tissue blood volume and oxygen saturation using biomedical optics techniques has the potential to inform the assessment of tissue health, healing, and dysfunction. These quantities are typically estimated from the contribution of oxyhemoglobin and deoxyhemoglobin to the absorption spectrum of the dermis. However, estimation of blood related absorption in superficial tissue such as the skin can be confounded by the strong absorption of melanin in the epidermis. Furthermore, epidermal thickness and pigmentation varies with anatomic location, race, gender, and degree of disease progression. This study describes a technique for decoupling the effect of melanin absorption in the epidermis from blood absorption in the dermis for a large range of skin types and thicknesses. An artificial neural network was used to map input optical properties to spatial frequency domain diffuse reflectance of two layer media. Then, iterative fitting was used to determine the optical properties from simulated spatial frequency domain diffuse reflectance. Additionally, an artificial neural network was trained to directly map spatial frequency domain reflectance to sets of optical properties of a two layer medium, thus bypassing the need for iteration. In both cases, the optical thickness of the epidermis and absorption and reduced scattering coefficients of the dermis were determined independently. The accuracy and efficiency of the iterative fitting approach was compared with the direct neural network inversion.

摘要

使用生物医学光学技术监测组织血液体积和氧饱和度有可能为评估组织健康、愈合和功能障碍提供信息。这些量通常是根据真皮的吸收光谱中氧合血红蛋白和脱氧血红蛋白的贡献来估计的。然而,在皮肤等浅层组织中,血液相关吸收的估计可能会受到表皮中黑色素强烈吸收的影响。此外,表皮厚度和色素沉着因解剖位置、种族、性别和疾病进展程度而异。本研究描述了一种用于在大范围皮肤类型和厚度下从真皮血液吸收中解耦表皮黑色素吸收影响的技术。人工神经网络用于将输入光学特性映射到两层介质的空间频域漫反射。然后,迭代拟合用于从模拟的空间频域漫反射确定光学特性。此外,还训练了一个人工神经网络,以便直接将空间频域反射率映射到两层介质的一组光学特性,从而无需迭代。在这两种情况下,表皮的光学厚度以及真皮的吸收和散射系数都被独立地确定。比较了迭代拟合方法和直接神经网络反演的准确性和效率。

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