TY - JOUR
T1 - Creation and validation of a chest X-ray dataset with eye-tracking and report dictation for AI development
AU - Karargyris, Alexandros
AU - Kashyap, Satyananda
AU - Lourentzou, Ismini
AU - Wu, Joy T.
AU - Sharma, Arjun
AU - Tong, Matthew
AU - Abedin, Shafiq
AU - Beymer, David
AU - Mukherjee, Vandana
AU - Krupinski, Elizabeth A.
AU - Moradi, Mehdi
N1 - Publisher Copyright:
© 2021, The Author(s).
PY - 2021/12
Y1 - 2021/12
N2 - We developed a rich dataset of Chest X-Ray (CXR) images to assist investigators in artificial intelligence. The data were collected using an eye-tracking system while a radiologist reviewed and reported on 1,083 CXR images. The dataset contains the following aligned data: CXR image, transcribed radiology report text, radiologist’s dictation audio and eye gaze coordinates data. We hope this dataset can contribute to various areas of research particularly towards explainable and multimodal deep learning/machine learning methods. Furthermore, investigators in disease classification and localization, automated radiology report generation, and human-machine interaction can benefit from these data. We report deep learning experiments that utilize the attention maps produced by the eye gaze dataset to show the potential utility of this dataset.
AB - We developed a rich dataset of Chest X-Ray (CXR) images to assist investigators in artificial intelligence. The data were collected using an eye-tracking system while a radiologist reviewed and reported on 1,083 CXR images. The dataset contains the following aligned data: CXR image, transcribed radiology report text, radiologist’s dictation audio and eye gaze coordinates data. We hope this dataset can contribute to various areas of research particularly towards explainable and multimodal deep learning/machine learning methods. Furthermore, investigators in disease classification and localization, automated radiology report generation, and human-machine interaction can benefit from these data. We report deep learning experiments that utilize the attention maps produced by the eye gaze dataset to show the potential utility of this dataset.
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U2 - 10.1038/s41597-021-00863-5
DO - 10.1038/s41597-021-00863-5
M3 - Article
C2 - 33767191
AN - SCOPUS:85103416457
VL - 8
JO - Scientific data
JF - Scientific data
SN - 2052-4463
IS - 1
M1 - 92
ER -