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Analysis of Multispectral Images of Excised Colon Tissue Samples Based on Genetic Algorithms

机译:基于遗传算法的切除结肠组织样品的多光谱图像分析

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We present in this paper a method to estimate four significant biological parameters of colon tissue. The interaction of light with colon tissue is modeled by two layers parameterized by biological parameters, which describe optical properties of the colon. This model is reversed using an optimization framework based on genetic algorithms. From a multispectral image of colon, we compute biological parameters of the colon, this noninvasive optical biopsy might lead to better diagnosis of cancer. We present in this paper experimental results analyzing multispectral images of excised colon tissue samples. We analyze the following three categories of colonic tissue: healthy tissue, with a polyp and with cancerous cells.
机译:我们在本文中存在一种估计结肠组织的四种显着生物参数的方法。通过通过生物参数参数化的两层模拟光子组织的相互作用,其描述了结肠的光学性质。使用基于遗传算法的优化框架来反转该模型。从结肠的多光谱图像,我们计算结肠的生物学参数,这种无侵入性光学活组织检查可能导致癌症更好地诊断。我们在本文中存在实验结果,分析了切除的结肠组织样品的多光谱图像。我们分析以下三类结肠组织:健康组织,用息肉和癌细胞。

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