Automated Microscope for Tuberculosis Detection

This project aims to design and develop an automated microscope system for tuberculosis (TB) detection using sputum smear samples. The system utilizes a microscope with motors for slide movement and lens auto-focusing, controlled by a microcontroller. The microscope captures images of the sputum samples and uses YOLOv5, a state-of-the-art object detection algorithm, to analyze the images for the presence of TB bacilli. The system can improve diagnostic accuracy, speed up the diagnostic process, and reduce the need for trained technicians. It can also be used for remote monitoring and telemedicine applications, enabling earlier detection and treatment of TB in resource-limited settings.