论文标题
使用胶囊神经网络预测无镜头显微镜图像中的结核病
Using Capsule Neural Network to predict Tuberculosis in lens-free microscopic images
论文作者
论文摘要
结核病是由一种称为结核分枝杆菌的细菌引起的，是全球最严重的公共卫生问题之一。这项工作旨在通过MODS方法促进和自动化结核病的预测，并使用无镜头显微镜，这很容易被未经训练的人员使用。我们在收集的数据集中采用了CAPSNET架构，并表明它的准确性比传统的CNN体系结构更好。
Tuberculosis, caused by a bacteria called Mycobacterium tuberculosis, is one of the most serious public health problems worldwide. This work seeks to facilitate and automate the prediction of tuberculosis by the MODS method and using lens-free microscopy, which is easy to use by untrained personnel. We employ the CapsNet architecture in our collected dataset and show that it has a better accuracy than traditional CNN architectures.
