DeepPulmoTB: Powering Robust Segmentation of Tuberculosis Lesions in Chest Computerized Tomography (CT) with Rich Annotations

Tuberculosis (TB) remains a major global health problem with high incidence and mortality rates worldwide. In recent years, with the rapid development of computer-aided diagnosis (CAD) tools, CAD has played an increasingly important role in supporting tuberculosis diagnosis. However, the development of CAD for TB diagnosis relies heavily on well-annotated computerized tomography (CT) datasets. Unfortunately, the currently available annotations in TB CT datasets are still limited, which hinders the development of CAD tools for TB diagnosis to some extent. To overcome this limitation, we introduce DeepPulmoTB, a CT multi-category semantic segmentation dataset specifically designed for TB with rich annotations. DeepPulmoTB encompasses three vital segmentation mask categories in TB diagnosis: consolidations, lung cavities, and both lungs. Furthermore, the annotations in DeepPulmoTB undergo meticulous review by professional physicians to ensure their high quality and reliability.