Tuberculosis Diagnosis and Visualization with a Large Vietnamese X-Ray Image Dataset  

作　　者：Nguyen Trong Vinh Lam Thanh Hien Ha Manh Toan Ngo Duc Vinh Do Nang Toan 

机构地区：[1]Faculty of Information Technology,Lac Hong University,Bien Hoa,Dong Nai,76120,Vietnam [2]Institute of Information Technology,Vietnam Academy of Science and Technology,Hanoi,10072,Vietnam [3]Faculty of Information Technology,Hanoi University of Industry,Hanoi,11915,Vietnam

出　　处：《Intelligent Automation & Soft Computing》2024年第2期281-299,共19页智能自动化与软计算（英文）

基　　金：funded by the Project KC-4.0.14/19-25“Research on Building a Support System for Diagnosis and Prediction Geo-Spatial Epidemiology of Pulmonary Tuberculosis by Chest X-Ray Images in Vietnam”.

摘　　要：Tuberculosis is a dangerous disease to human life,and we need a lot of attempts to stop and reverse it.Significantly,in theCOVID-19 pandemic,access to medical services for tuberculosis has become very difficult.The late detection of tuberculosis could lead to danger to patient health,even death.Vietnamis one of the countries heavily affected by the COVID-19 pandemic,andmany residential areas as well as hospitals have to be isolated for a long time.Reality demands a fast and effective tuberculosis diagnosis solution to deal with the difficulty of accessingmedical services,such as an automatic tuberculosis diagnosis system.In our study,aiming to build that system,we were interested in the tuberculosis diagnosis problem from the chest X-ray images of Vietnamese patients.The chest X-ray image is an important data type to diagnose tuberculosis,and it has also received a lot of attention from deep learning researchers.This paper proposed a novel method for tuberculosis diagnosis and visualization using the deeplearning approach with a large Vietnamese X-ray image dataset.In detail,we designed our custom convolutional neural network for the X-ray image classification task and then analyzed the predicted result to provide visualization as a heat-map.To prove the performance of our network model,we conducted several experiments to compare it to another study and also to evaluate it with the dataset of this research.To support the implementation,we built a specific annotation system for tuberculosis under the requirements of radiologists in the Vietnam National Lung Hospital.A large experiment dataset was also from this hospital,and most of this data was for training the convolutional neural network model.The experiment results were evaluated regarding sensitivity,specificity,and accuracy.We achieved high scores with a training accuracy score of 0.99,and the testing specificity and sensitivity scores were over 0.9.Based on the X-ray image classification result,we visualize prediction results as heat-maps and also analyze t

关 键 词：Tuberculosis classification Vietnamese chest X-ray deep learning 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] R52[自动化与计算机技术—计算机科学与技术]