Enhancing tuberculosis diagnosis: A deep learning-based framework for accurate detection and quantification of TB bacilli in microscopic images

The system achieved a mean receiver operating characteristic score of 0.9505, a precision of 0.924, a recall of 0.882, and an F1 score of 0.902, demonstrating its potential to improve TB screening, particularly in resource-limited settings. By minimizing reliance on skilled technicians and enhancing diagnostic reliability, this approach offers a scalable solution for effective TB detection and severity assessment.