Classification of X-ray Images for Pulmonary Diseases Using Deep Learning Techniques
Keywords:
Convolutional Neural Network (CNN), pulmonary diseases, Chest X-ray (CXR), Tuberculosis, Deep Learning (DL), Pneumonia, Recurrent Neural Network (RNN), Covid-19Abstract
In the present day, a chest x-ray is the most effective method for distinguishing different pulmonary diseases, however finding multiple pulmonary diseases can be very challenging, especially in places where gifted radiologists are hard to reach. The chest X-ray cannot diagnose many lung disorders because they often resemble one another. Due to the increasing mortality rate and insufficient health supplies, hospitals and radiologists across the globe have been working tirelessly to diagnose patients. Using deep learning systems, it is possible to distinguish pneumonia, tuberculosis, and covid-19 from chest x-rays with advances in automation. Clinical nursing and observational studies are indispensable when chest x-rays are required, although we cannot ignore the conditions leading to the illness where pneumonia, TB, and covid-19 are extreme categories. By automating pulmonary diseases classification based on chest X-rays, we are able to identify pneumonia, TB, covid-19 allowing for quicker intervention and improved accuracy.
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