Eye Gaze Data for Chest X-rays

We created a rich multimodal dataset for the Chest X-Ray (CXR) domain. The data was collected using an eye tracking system while a radiologist interpreted and read 1,083 public CXR images. The dataset contains the following aligned modalities: image, transcribed report text, dictation audio and eye gaze data. We hope this dataset can contribute to various fields of research with applications in machine learning such as deep learning explainability, multi-modal fusion, disease classification, and automated radiology report generation to name a few. The images were selected from the MIMIC-CXR Database and were associated with studies from 1,038 subjects (female: 495, male: 543) who had age range 20 - 80 years old.

本团队精心构建了一个丰富的多模态数据集，专注于胸部X射线（CXR）领域。数据采集过程中，借助眼动追踪系统，由放射科医师对1,083张公开的CXR图像进行解读与分析。该数据集包含以下对齐的模态：图像、转录的报告文本、语音记录音频以及眼动数据。我们期望该数据集能够为众多研究领域提供助力，其在机器学习领域的应用包括深度学习可解释性、多模态融合、疾病分类以及自动化放射学报告生成等诸多方面。所选图像源自MIMIC-CXR数据库，并关联了1,038位受试者的研究资料（女性495名，男性543名），受试者年龄介于20至80岁之间。