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.

搜集汇总

背景与挑战

背景概述

VinDr-PCXR是一个开放的大规模儿科胸部X光数据集，包含9,125个扫描，由越南一家儿科医院在2020-2021年收集，每个扫描由放射科医生手动标注了36个关键发现和15种疾病，包括病变级别和图像级别的标签。该数据集旨在支持儿科胸部疾病的诊断算法开发，分为7,728个训练样本和1,397个测试样本，是目前首个且最大的儿科CXR多标签标注数据集。