Deep learning for chest X-ray analysis: A survey

Recent advances in deep learning have led to a promising performance many medical image analysis tasks. As the most commonly performed radiological exam, chest radiographs are particularly important modality for which variety of applications been researched. The release multiple, large, publicly available X-ray datasets recent years has encouraged research interest and boosted number publications. In this paper, we review all studies using on published before March 2021, categorizing works by task: image-level prediction (classification regression), segmentation, localization, generation domain adaptation. Detailed descriptions included commercial systems field described. A comprehensive discussion current state art is provided, including caveats use public datasets, requirements clinically useful gaps literature.