Learning to Read Chest X-Rays: Recurrent Neural Cascade Model for Automated Image Annotation

@article{Shin2016LearningTR,
  title={Learning to Read Chest X-Rays: Recurrent Neural Cascade Model for Automated Image Annotation},
  author={Hoo-Chang Shin and Kirk Roberts and Le Lu and Dina Demner-Fushman and Jianhua Yao and R. Summers},
  journal={2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2016},
  pages={2497-2506}
}
  • Hoo-Chang Shin, Kirk Roberts, +3 authors R. Summers
  • Published 2016
  • Computer Science
  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • Despite the recent advances in automatically describing image contents, their applications have been mostly limited to image caption datasets containing natural images (e.g., Flickr 30k, MSCOCO). In this paper, we present a deep learning model to efficiently detect a disease from an image and annotate its contexts (e.g., location, severity and the affected organs). We employ a publicly available radiology dataset of chest x-rays and their reports, and use its image annotations to mine disease… CONTINUE READING
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