Detecting Campylobacter Bacteria and Phagocytotic Activity of Leukocytes from Gram Stained Smears Images

Kyohei Yoshihara, K. Hirata
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引用次数: 3

Abstract

In this paper, we develop the method to detect Campylobacter bacteria and phagocytotic activity of leukocytes from Gram stained smears images. First, we improve VGG16 by adding batch normalization and by replacing flatten with global average pooling and construct the classifier by using transfer learning model based on the improved VGG16. Then, by comparing the detection by the VGG16 with that by the improved VGG16, for the classification of Camphylobacter bacteria, we give experimental results of classifying Campylobacter images with non-Campylobacter images. On the other hand, for the classification of phagocytotic activity of leukocytes, we give experimental results of classifying phagocytotic images with quasi- and non-phagocytotic images and of classifying phagocytotic images, quasi-phagocytotic images and non-phagocytotic images.
革兰氏染色涂片图像检测弯曲杆菌、细菌和白细胞吞噬活性
本文建立了革兰氏染色涂片图像中弯曲杆菌和白细胞吞噬活性的检测方法。首先,对VGG16进行改进,加入批处理归一化,用全局平均池化代替平面化,并在改进后的VGG16基础上使用迁移学习模型构建分类器。然后,通过比较改进的VGG16和VGG16对弯曲杆菌的检测结果,给出了弯曲杆菌图像与非弯曲杆菌图像分类的实验结果。另一方面,对于白细胞吞噬活性的分类,我们给出了将吞噬图像分为准吞噬图像和非吞噬图像以及将吞噬图像、准吞噬图像和非吞噬图像进行分类的实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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