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用于口腔检测的RGB发光二极管的最佳照明

Optimal lighting of RGB LEDs for oral cavity detection.

作者信息

Wang Hsiang-Chen, Chen Yung-Tsan

机构信息

Graduate Institute of Opto-Mechatronics, National Chung Cheng University 168, University Rd., Min-Hsiung, Chia-Yi 62102, Taiwan.

出版信息

Opt Express. 2012 Apr 23;20(9):10186-99. doi: 10.1364/OE.20.010186.

DOI:10.1364/OE.20.010186
PMID:22535110
Abstract

In this paper the optimal lighting for oral cavity detection is proposed. The illuminants consist of several LEDs with different intensity ratios and peak wavelengths, which can enhance the color difference between normal and abnormal regions in the oral cavity. An algorithm combined with multi-spectral imaging (MSI) and color reproduction technique is applied to find the best enhancement of this difference. The colored LEDs of the optimal lighting, the Color Rendering Index (CRI) of the illuminants, and comparison with traditional illuminants are discussed. The calculations show that color enhancement ability in the oral cavity is not entirely a function of the higher CRI of some illuminants, as the narrowband illuminants (LEDs) produce an image with greater contrast than the broadband spectra and higher CRI of traditional illuminants in the reddish oral environment. Accordingly, an illuminant with specific intensity ratio of red, green, and blue LEDs is proposed, which has optimal color enhancement for oral cavity detection. Compared with the fluorescent lighting commonly in the use now, the color difference between normal and inflamed tissues can be improved from 21.5732 to 30.5532, a 42% increase, thus making medical diagnosis more efficient, so helping patients receive early treatment.

摘要

本文提出了用于口腔检测的最佳照明方案。照明光源由几个具有不同强度比和峰值波长的发光二极管组成,可增强口腔正常区域与异常区域之间的色差。应用一种结合多光谱成像(MSI)和色彩还原技术的算法来找到这种差异的最佳增强效果。讨论了最佳照明的彩色发光二极管、照明光源的显色指数(CRI)以及与传统照明光源的比较。计算结果表明,口腔中的色彩增强能力并不完全取决于某些照明光源较高的显色指数,因为在微红的口腔环境中,窄带照明光源(发光二极管)产生的图像对比度比宽带光谱和传统照明光源较高显色指数产生的图像对比度更大。因此,提出了一种具有特定红、绿、蓝发光二极管强度比的照明光源,其对口腔检测具有最佳的色彩增强效果。与目前常用的荧光照明相比,正常组织与发炎组织之间的色差可从21.5732提高到30.5532,增加了42%,从而提高了医学诊断效率,有助于患者尽早接受治疗。

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