PediCXR: An open, large-scale chest radiograph dataset for interpretation of common thoracic diseases in children

TL;DR

PediCXR is the first large-scale pediatric chest X-ray dataset with detailed annotations, designed to facilitate the development of diagnostic models for thoracic diseases in children.

Contribution

This paper introduces PediCXR, a comprehensive, annotated pediatric CXR dataset, filling a critical gap for data-driven pediatric disease diagnosis research.

Findings

Largest pediatric CXR dataset with lesion-level annotations

Includes 36 findings and 15 diseases with bounding boxes

Publicly available for research and development

Abstract

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 PediCXR, a new pediatric CXR dataset of 9,125 studies retrospectively collected from a major pediatric hospital in Vietnam between 2020 and 2021. Each scan was manually annotated by a pediatric radiologist with more than ten years of experience. The dataset was labeled 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 annotations and image-level labels for the detection of multiple findings and diseases. For algorithm development, the dataset was divided into a training set of 7,728 and a test set of 1,397. To encourage new advances in pediatric CXR interpretation using data-driven approaches, we provide a detailed description of the PediCXR data sample and make the dataset publicly available on https://physionet.org/content/pedicxr/1.0.0/