Detection Of Pulmonary Diseases in Lung Using CT & X-ray Images CNN

Abstract

This study presents a deep learning approach utilizing Convolutional Neural Networks (CNNs) for the detection of pulmonary diseases from CT and X-ray images. With the rising prevalence of respiratory illnesses, accurate and efficient diagnosis is crucial for timely treatment. The proposed CNN framework leverages its ability to automatically learn discriminative features from medical images, enabling robust disease detection. By training on a diverse dataset comprising CT and X-ray scans, the model achieves high sensitivity and specificity in identifying common pulmonary conditions such as Covid-19 & Effusion Disease. The results demonstrate the potential of CNNs as a valuable tool in the early detection and management of respiratory diseases, contributing to improved patient outcomes and healthcare delivery.