Medical University of Graz, Department of Radiology, Division of Pediatric Radiology, Graz, Austria.
Medical University of Graz, Department of Radiology, Division of General Radiology, Graz, Austria.
Sci Data. 2022 May 20;9(1):222. doi: 10.1038/s41597-022-01328-z.
Digital radiography is widely available and the standard modality in trauma imaging, often enabling to diagnose pediatric wrist fractures. However, image interpretation requires time-consuming specialized training. Due to astonishing progress in computer vision algorithms, automated fracture detection has become a topic of research interest. This paper presents the GRAZPEDWRI-DX dataset containing annotated pediatric trauma wrist radiographs of 6,091 patients, treated at the Department for Pediatric Surgery of the University Hospital Graz between 2008 and 2018. A total number of 10,643 studies (20,327 images) are made available, typically covering posteroanterior and lateral projections. The dataset is annotated with 74,459 image tags and features 67,771 labeled objects. We de-identified all radiographs and converted the DICOM pixel data to 16-Bit grayscale PNG images. The filenames and the accompanying text files provide basic patient information (age, sex). Several pediatric radiologists annotated dataset images by placing lines, bounding boxes, or polygons to mark pathologies like fractures or periosteal reactions. They also tagged general image characteristics. This dataset is publicly available to encourage computer vision research.
数字射线摄影在创伤成像中得到广泛应用，是标准的模态，通常能够诊断儿科腕骨骨折。然而，图像解释需要耗时的专业培训。由于计算机视觉算法的惊人进步，自动骨折检测已成为研究热点。本文介绍了 GRAZPEDWRI-DX 数据集，其中包含了 6091 名在 2008 年至 2018 年期间在格拉茨大学医院小儿外科接受治疗的小儿创伤腕骨射线照片。总共提供了 10643 项研究（20327 张图像），通常涵盖前后位和侧位投影。该数据集标注了 74459 个图像标签，包含 67771 个标记对象。我们对所有射线照片进行了去识别处理，并将 DICOM 像素数据转换为 16 位灰度 PNG 图像。文件名和附带的文本文件提供了基本的患者信息（年龄、性别）。几位儿科放射科医生通过放置线条、边界框或多边形来标记骨折或骨膜反应等病变，对数据集图像进行了标注。他们还标记了一般的图像特征。该数据集可供公众使用，以鼓励计算机视觉研究。
