Abstract:
The project aims to develop a CNN model for classifying X-ray images. In this
report, we introduced a deep learning-based approach to automatically detect the
manifestations oftuberculosis using chest X-rays. Pakistan is the country with the
highest exposure to TB cases.
Chest X-rays are used to diagnose active tuberculosis in symptomatic patients. This
method ofscreening is ideally performed in primary health centres where clinicians
are available and sometimes by portable X-ray machine. The main challenge ofthis
screening method is timely reporting and follow-up ofthe patient at the beginning of
treatment. We have created a convolutional neural network to model automated
tuberculosis diagnosis, an advanced deep learning algorithm.
The suggested method will automatically detect whether the given image is infected
with TB or not. This method helps doctors to make accurate predictions ofthe
disease in a short period oftime, thus helping to improve the clinical outcome.
