Lungscan Intelligent Detection of Pulmonary Diseases

With the growing need for faster and more accurate diagnosis in the medical field, especially in radiology, this project introduces a Pneumonia Detection Web Application that helps automate the identification of pneumonia from chest X-ray images. Built using deep learning, the system uses a convolutional neural network (CNN) trained to differentiate between normal and pneumonia-affected lungs. The application allows users—primarily clinicians or radiologists—to upload an X-ray image through a clean and responsive interface built with React.js. Once uploaded, the image is sent to a Flask-based backend where it is preprocessed and analyzed by the trained model. The result, indicating whether the image shows signs of pneumonia, is then displayed to the user along with a confidence score. This tool aims to assist healthcare professionals in making quicker and more reliable diagnoses, especially in settings where expert interpretation may not always be available. The system's design focuses on usability, speed, and accuracy, making it a valuable addition to modern diagnostic workflows.