{"title":"从胸部x线图像诊断COVID-19感染肺部","authors":"T. R. Niloy, A. Rahman","doi":"10.53799/ajse.v20i1.142","DOIUrl":null,"url":null,"abstract":"Severe Acute Respiratory Symptom Coronavirus 2 (SARS-CoV-2) was newly discovered as a beta coronavirus. The virus-induced unexplained etiological pneumonia and is referred to as the 2019 Coronavirus Disease (COVID-19). Though the disease has appeared in a new way, there is no medication for transited patients. So, for diagnosing the COVID-19 infected lungs from X-Ray images, an automated technique has been suggested in this manuscript. In this study, Convolutional neural network (CNN) and VGG19 were used and found accuracy scores of 97% and 67%, respectively. The comparative analysis shows that the proposed method performs better than the solution that exists. Eventually, Precision, Recall, and F1-Score have been extracted and interpreted the model's loss functions in the research. This research has carried out by focusing on essential aspects in terms of COVID-19. Therefore, for the diagnosis of coronavirus infection, the technique can be used effectively.","PeriodicalId":224436,"journal":{"name":"AIUB Journal of Science and Engineering (AJSE)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Diagnosis of COVID-19 Infected Lungs from Chest X-Ray Images\",\"authors\":\"T. R. Niloy, A. Rahman\",\"doi\":\"10.53799/ajse.v20i1.142\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Severe Acute Respiratory Symptom Coronavirus 2 (SARS-CoV-2) was newly discovered as a beta coronavirus. The virus-induced unexplained etiological pneumonia and is referred to as the 2019 Coronavirus Disease (COVID-19). Though the disease has appeared in a new way, there is no medication for transited patients. So, for diagnosing the COVID-19 infected lungs from X-Ray images, an automated technique has been suggested in this manuscript. In this study, Convolutional neural network (CNN) and VGG19 were used and found accuracy scores of 97% and 67%, respectively. The comparative analysis shows that the proposed method performs better than the solution that exists. Eventually, Precision, Recall, and F1-Score have been extracted and interpreted the model's loss functions in the research. This research has carried out by focusing on essential aspects in terms of COVID-19. Therefore, for the diagnosis of coronavirus infection, the technique can be used effectively.\",\"PeriodicalId\":224436,\"journal\":{\"name\":\"AIUB Journal of Science and Engineering (AJSE)\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AIUB Journal of Science and Engineering (AJSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.53799/ajse.v20i1.142\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AIUB Journal of Science and Engineering (AJSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53799/ajse.v20i1.142","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Diagnosis of COVID-19 Infected Lungs from Chest X-Ray Images
Severe Acute Respiratory Symptom Coronavirus 2 (SARS-CoV-2) was newly discovered as a beta coronavirus. The virus-induced unexplained etiological pneumonia and is referred to as the 2019 Coronavirus Disease (COVID-19). Though the disease has appeared in a new way, there is no medication for transited patients. So, for diagnosing the COVID-19 infected lungs from X-Ray images, an automated technique has been suggested in this manuscript. In this study, Convolutional neural network (CNN) and VGG19 were used and found accuracy scores of 97% and 67%, respectively. The comparative analysis shows that the proposed method performs better than the solution that exists. Eventually, Precision, Recall, and F1-Score have been extracted and interpreted the model's loss functions in the research. This research has carried out by focusing on essential aspects in terms of COVID-19. Therefore, for the diagnosis of coronavirus infection, the technique can be used effectively.