Attention-Guided Convolutional Neural Network for Detecting Pneumonia on Chest X-Rays.

Journal: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Published Date:

Abstract

Pneumonia is a common infectious disease in the world. Its main diagnostic method is chest X-ray (CXR) examination. However, the high visual similarity between a large number of pathologies in CXR makes the interpretation and differentiation of pneumonia a challenge. In this paper, we propose an improved convolutional neural network (CNN) model for pneumonia detection. In order to guide the CNN to focus on disease-specific attended region, the pneumonia area of image is erased and marked as a non-pneumonia sample. In addition, transfer learning is used to segment the interest region of lungs to suppress background interference. The experimental results show that the proposed method is superior to the state-of-the-art object detection model in terms of accuracy and false positive rate.

Authors

  • Bingchuan Li
  • Guixia Kang
    School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China.
  • Kai Cheng
    Department of Radiation Oncology, Stanford University, Stanford, California.
  • Ningbo Zhang
    School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China.