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Detection of H. pylori induced gastric inflammation by diffuse reflectance analysis

机译:弥漫性反射率分析的幽门螺杆菌诱导胃炎的检测

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Spectral acquisitions contain rich information and thus, are promising modalities for early detection of gastric diseases. In this study, we analyze the diffuse reflectance of the gastric inflammatory lesions induced by the bacterium H. pylori in the mouse stomach. A pipeline has been designed to characterize and classify spectra acquired on mice. The pipeline is based on a band clustering algorithm followed by the computation of meaningful division and subtraction features and by classification with a linear SVM classifier. Currently, the pipeline is able to recognize inflamed stomachs spectra with an accuracy of 98%. These results are promising and the same pipeline could be adapted for the study of gastric pathologies in humans.
机译:光谱采集含有丰富的信息,因此是早期检测胃病的有希望的方式。在这项研究中,我们分析了小鼠胃中的细菌H.幽门诱导的胃炎病变的弥漫反射率。一条管道旨在表征和分类在小鼠上获得的光谱。管道基于乐队聚类算法,然后通过用线性SVM分类器进行分类和减法特征来计算有意义的分割和减法特征。目前,管道能够以98%的精度识别发炎胃谱。这些结果是有前途的,同样的管道可以适应人类胃病的研究。

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