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.成人胸部X线摄影（Chest Radiography, CXR）的计算机辅助诊断系统近年来凭借大规模标注数据集的问世与高性能监督学习算法的突破，取得了长足进展。然而，针对儿童胸部X线扫描中的儿科疾病检测与诊断模型开发，却因缺乏高质量的医师标注数据集而步履维艰。为攻克这一难题，本文提出并公开了一款全新的儿科CXR数据集：该数据集共包含9125份检查样本，于2020至2021年间从越南一家大型儿科医院回顾性收集而来。每份扫描图像均由经验丰富的放射科医师手动标注，标记了36种关键异常征象与15种疾病的存在情况，其中每一处异常征象均通过图像上的矩形边界框完成定位。据我们所知，本数据集是首个且规模最大的同时涵盖多征象、多疾病的病灶级标签与图像级标签的儿科胸部X线摄影数据集。为支撑算法研发，该数据集被划分为包含7728份样本的训练集与1397份样本的测试集。

搜集汇总

背景与挑战

背景概述

VinDr-PCXR是一个大规模儿科胸部X光数据集，包含9,125个10岁以下患者的X光扫描图像，专门用于常见胸部疾病的诊断。该数据集提供了36个关键发现和15种疾病的手动标注，包括病灶级边界框标注和图像级标签，分为7,728个训练样本和1,397个测试样本，旨在支持儿科胸部X光计算机辅助诊断系统的开发。