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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本多光谱图像分析

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摘要

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:我们在本文中提出了一种估计结肠组织四个重要生物学参数的方法。光线与结肠组织的相互作用是由生物学参数设置的两层模型化的,这些参数描述了结肠的光学特性。使用基于遗传算法的优化框架可以逆转此模型。从结肠的多光谱图像,我们计算结肠的生物学参数,这种无创光学活检可能会导致更好的癌症诊断。我们在本文中提供的实验结果分析了切除的结肠组织样本的多光谱图像。我们分析了结肠组织的以下三类:具有息肉和癌细胞的健康组织。

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