The invention provides a novel, AI-powered solution for the automated detection and quantification of emphysema using CT thorax imaging. Emphysema, a major component of Chronic Obstructive Pulmonary Disease (COPD), is traditionally assessed through manual interpretation of CT scans, which is time-consuming, subjective, and prone to interobserver variability. This invention addresses these limitations by introducing an application/API module that integrates advanced AI algorithms with existing medical imaging systems.

The core of the invention is an AI-based mobile application and API interface designed to process CT thorax images, enabling precise analysis of lung parenchyma. The AI algorithms are trained on extensive datasets to detect subtle patterns of emphysema, classify subtypes, and provide quantitative metrics of disease severity and progression. Results are delivered in real time, ensuring prompt feedback for clinical decision-making.

The system is equipped with a user-friendly mobile interface that facilitates seamless uploading of CT images, real-time processing via cloud-based infrastructure, and intuitive presentation of results. It is scalable, adaptable to diverse healthcare settings, and supports integration with existing imaging workflows, enabling widespread adoption. Additionally, the invention provides opportunities for use in telemedicine, remote consultations, and longitudinal disease monitoring.