漫反射分析法检测幽门螺杆菌性胃炎

Alexandre Krebs, V. Camilo, E. Touati, Y. Benezeth, V. Michel, G. Jouvion, Fan Yang, D. Lamarque, F. Marzani
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引用次数: 1

摘要

光谱采集包含丰富的信息,因此是早期发现胃部疾病的有希望的方式。在这项研究中,我们分析了幽门螺杆菌在小鼠胃中引起的胃炎性病变的漫反射。设计了一个管道来表征和分类在小鼠身上获得的光谱。该管道基于带聚类算法,然后计算有意义的除法和减法特征,并使用线性支持向量机分类器进行分类。目前,该管道能够以98%的准确率识别炎症胃的光谱。这些结果是有希望的,同样的管道可以适用于人类胃病理的研究。
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[Regular Paper] Detection of H. pylori Induced Gastric Inflammation by Diffuse Reflectance Analysis
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 stomach's 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.
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