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Image reconstruction of the location of macro-inhomogeneity in random turbid medium by using artificial neural networks

机译:用人工神经网络改造随机混浊介质中宏观偏近均匀性位置的重建

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Nowadays the artificial neural network (ANN), an effective powerful technique that is able denoting complex input and output relationships, is widely used in different biomedical applications. In present study the applying of ANN for the determination of characteristics of random highly scattering medium (like bio-tissue) is considered. Spatial distribution of the backscattered light calculated by Monte Carlo method is used to train ANN for multiply scattering regimes. The potential opportunities of use of ANN for image reconstruction of an absorbing macro inhomogeneity located in topical layers of random scattering medium are presented. This is especially of high priority because of new diagnostics/treatment developing that is based on the applying gold nano-particles for labeling cancer cells.
机译:如今,人工神经网络(ANN),一种能够表示复杂输入和输出关系的有效强大技术,广泛用于不同的生物医学应用。在本研究中,考虑了用于测定随机高度散射培养基(如生物组织)的测定的ANN。 Monte Carlo方法计算的背散射光的空间分布用于训练ANN以进行乘法散射制度。呈现了在随机散射介质局部层的吸收宏观均匀性的图像重建使用ANN的潜在机会。由于新的诊断/治疗开发,这尤其是高优先级,这是基于用于标记癌细胞的施加金纳米颗粒的新诊断/治疗。

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