An ultra-wide-field fundus image dataset for intelligent diagnosis of intraocular tumors

This dataset consisted of 2,031 ultra-wide-field fundus images, encompassing five distinct types of intraocular tumors and normal images. It is provided as a zipped file containing six subfolders, each corresponding to a specific category: Normal, Choroidal Hemangioma (CH), Retinal Capillary Hemangioma (RCH), Choroidal Osteoma (CO), Retinoblastoma (RB), and Uveal Melanoma (UM). Each subfolder includes all the fundus images belonging to its respective category. The dataset is designed to facilitate the development of AI algorithms aimed at automating the detection of intraocular tumors.