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Feature and Deep Learning Based Approaches for Automatic Report Generation and Severity Scoring of Lung Tuberculosis from CT Images

The paper presents two approaches for automatic Computed Tomography (CT) report and tuberculosis (TB) severity scoring which were two subtasks of ImageCLEFtuberculosis 2019 challenge. While our first approach uses image processing techniques for feature extraction from CT scans, our second approach uses artificial neural networks (ANN) for predicting probabilities for different lung irregularities associated with pulmonary tuberculosis and tuberculosis severity assessment. The results showed that our feature-based approach is still a competitive method that achieved rank 3 of 54 in the severity scoring subtask and rank 7 of 35 in the CT report subtask.