Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualization

Tuberculosis (TB) is a chronic lung disease that occurs due to bacterial infection and is one of the top 10 leading causes of death. Accurate and early detection of TB is very important, otherwise, it could be life-threatening. In this work, we have detected TB reliably from the chest X-ray images using image pre-processing, data augmentation, image segmentation, and deep-learning classification techniques. Several public databases were used to create a database of 3500 TB infected and 3500 normal chest X-ray images for this study. Nine different deep CNNs (ResNet18, ResNet50, ResNet101, ChexNet, InceptionV3, Vgg19, DenseNet201, SqueezeNet, and MobileNet) were used for transfer learning from their pre-trained…

• QF
  Qatar Foundation

  Award: NPRP12S-0227-190164
• FN
  Fonds National de la Recherche Luxembourg
• QN
  Qatar National Research Fund

  Awards: NPRP12S-0227-190164, NPRP12S-
• QN
  Qatar National Library