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.

本团队构建了一套面向胸部X射线（Chest X-Ray，CXR）领域的丰富多模态数据集。该数据集的数据采集依托眼动追踪系统完成，期间一名放射科医师对1083张公开的CXR图像进行阅片与诊断解读。本数据集包含以下对齐后的多模态数据类型：影像、转录后的报告文本、口述音频以及眼动追踪数据。本团队期望该数据集能够为多领域研究提供支撑，其可应用于机器学习相关方向，例如深度学习可解释性、多模态融合、疾病分类以及自动化放射学报告生成等诸多场景。本次选用的影像源自MIMIC-CXR数据库，相关研究涉及1038名受试者，其中女性495名、男性543名，年龄跨度为20至80岁。

搜集汇总

背景与挑战

背景概述

该数据集是一个多模态的胸部X光片（CXR）眼动追踪数据集，包含1,083张CXR图像及其相关的眼动数据、口述音频和转录文本。数据集旨在支持机器学习研究，特别是在深度学习可解释性和多模态融合方面。