Open ultrawidefield fundus image dataset with disease diagnosis and clinical image quality assessment.

Autor: He S; Department of Ophthalmology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China., Ye X; Zhejiang Provincial People's Hospital Bijie Hospital, Bijie, Guizhou, China. yexinsarah@163.com., Xie W; Zhejiang Provincial People's Hospital Bijie Hospital, Bijie, Guizhou, China., Shen Y; Department of Ophthalmology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China., Yang S; Wenzhou Medical University, Wenzhou, Zhejiang, China., Zhong X; Wenzhou Medical University, Wenzhou, Zhejiang, China., Guan H; Wenzhou Medical University, Wenzhou, Zhejiang, China., Zhou X; Wenzhou Medical University, Wenzhou, Zhejiang, China., Wu J; Hangzhou Medical College, Hangzhou, Zhejiang, China., Shen L; Department of Ophthalmology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China. slj@mail.eye.ac.cn.; Wenzhou Medical University, Wenzhou, Zhejiang, China. slj@mail.eye.ac.cn.; Hangzhou Medical College, Hangzhou, Zhejiang, China. slj@mail.eye.ac.cn.
Jazyk: angličtina
Zdroj: Scientific data [Sci Data] 2024 Nov 20; Vol. 11 (1), pp. 1251. Date of Electronic Publication: 2024 Nov 20.
DOI: 10.1038/s41597-024-04113-2
Abstrakt: Ultrawidefield fundus (UWF) images have a wide imaging range (200° of the retinal region), which offers the opportunity to show more information for ophthalmic diseases. Image quality assessment (IQA) is a prerequisite for applying UWF and is crucial for developing artificial intelligence-driven diagnosis and screening systems. Most image quality systems have been applied to the assessments of natural images, but whether these systems are suitable for evaluating the UWF image quality remains debatable. Additionally, existing IQA datasets only provide photographs of diabetic retinopathy (DR) patients and quality evaluation results applicable for natural image, neglecting patients' clinical information. To address these issues, we established a real-world clinical practice ultra-widefield fundus images dataset, with 700 high-resolution UWF images and corresponding clinical information from six common fundus diseases and healthy volunteers. The image quality is annotated by three ophthalmologists based on the field of view, illumination, artifact, contrast, and overall quality. This dataset illustrates the distribution of UWF image quality across diseases in clinical practice, offering a foundation for developing effective IQA systems.
Competing Interests: Competing interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(© 2024. The Author(s).)
Databáze: MEDLINE
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