Artificial Intelligence-Based Classification of Chest X-Ray Images into COVID-19 and Other Infectious Diseases.
Artificial Intelligence-Based Classification of Chest X-Ray Images into COVID-19 and Other Infectious Diseases.
复制标题
DOI：
10.1155/2020/8889023
复制
发表时间：
2020
影响因子：
7.6
通讯作者：
Gupta D
中科院分区：
文献类型：
--
作者：
Sharma A;Rani S;Gupta D
持续的2019冠状病毒病（COVID-19）大流行除了带来巨大的社会经济影响外，还导致全球健康和医疗危机。在这场危机中，其中一个重大挑战是快速有效地识别和监测COVID-19患者，以便及时做出治疗、监测和管理的决定。研究工作正在开发耗时更少的方法来取代或补充基于RT-PCR的方法。本研究旨在创建高效的深度学习模型，使用胸部X光图像进行训练，以快速筛查COVID-19患者。我们使用公开可用的成人COVID-19患者的PA胸部X射线图像，用于开发COVID-19和其他主要传染病的基于人工智能（AI）的分类模型。为了增加数据集大小并开发通用模型，我们对原始图像进行了25种不同类型的增强。此外，我们利用迁移学习方法来训练和测试分类模型。两个表现最好的模型（每个模型在286张图像上训练，旋转120°或140°）的组合显示出对正常、COVID-19、非COVID-19、肺炎和结核病图像的最高预测准确率。通过迁移学习方法训练的基于AI的分类模型可以有效地对代表所研究疾病的胸部X射线图像进行分类。我们的方法比以前公布的方法更有效。这是实现基于AI的方法来解决与COVID-19相关的生物医学成像分类问题的一步。
The ongoing pandemic of coronavirus disease 2019 (COVID-19) has led to global health and healthcare crisis, apart from the tremendous socioeconomic effects. One of the significant challenges in this crisis is to identify and monitor the COVID-19 patients quickly and efficiently to facilitate timely decisions for their treatment, monitoring, and management. Research efforts are on to develop less time-consuming methods to replace or to supplement RT-PCR-based methods. The present study is aimed at creating efficient deep learning models, trained with chest X-ray images, for rapid screening of COVID-19 patients. We used publicly available PA chest X-ray images of adult COVID-19 patients for the development of Artificial Intelligence (AI)-based classification models for COVID-19 and other major infectious diseases. To increase the dataset size and develop generalized models, we performed 25 different types of augmentations on the original images. Furthermore, we utilized the transfer learning approach for the training and testing of the classification models. The combination of two best-performing models (each trained on 286 images, rotated through 120° or 140° angle) displayed the highest prediction accuracy for normal, COVID-19, non-COVID-19, pneumonia, and tuberculosis images. AI-based classification models trained through the transfer learning approach can efficiently classify the chest X-ray images representing studied diseases. Our method is more efficient than previously published methods. It is one step ahead towards the implementation of AI-based methods for classification problems in biomedical imaging related to COVID-19.