VinDr-PCXR: An open, large-scale pediatric chest X-ray dataset for interpretation of common thoracic diseases

Computer-aided diagnosis systems in adult chest radiography (CXR) have
recently achieved great success thanks to the availability of large-scale,
annotated datasets and the advent of high-performance supervised learning
algorithms. However, the development of diagnostic models for detecting and
diagnosing pediatric diseases in CXR scans is undertaken due to the lack of
high-quality physician-annotated datasets. To overcome this challenge, we
introduce and release in this paper a new pediatric CXR dataset of 9,125
studies that were retrospectively collected from a major pediatric hospital in
Vietnam between 2020-2021. Each scan was manually annotated by an experienced
radiologist for the presence of 36 critical findings and 15 diseases. In
particular, each abnormal finding was identified via a rectangle bounding box
on the image. To the best of our knowledge, this is the first and largest
pediatric CXR dataset containing lesion-level labels and image-level labels
for multiple findings and diseases. For algorithm development, the dataset is
divided into a training set of 7,728 and a test set of 1,397.