2026-10-14T11:45:33Z https://www.scidb.cn/oai

10.57760/sciencedb.18735 2025-05-06T09:30:52Z

2025-05-06 LCFP-14M: A High-quality Large-scale Color Fundus Photography Images Dataset with Eleven Types of Annotations doi:10.57760/sciencedb.18735 en More and more human beings are suffering from ophthalmic diseases, and automatic analysis of images from Color Fundus Photography (CFP) using deep learning algorithms can improve the accuracy and prevalence of early screening for ophthalmic diseases. However, the performance of deep learning models is highly dependent on the training data, and the currently available retinal image datasets still have limitations such as scarce total data and poor disease diversity. Therefore, we extensively collected and integrated the CFP publicly available datasets, resulting in the construction LCFP-14M dataset containing 13,718,610 retinal fundus images with a total of 150,904,710 annotations, which is one of the largest datasets and covers the widest range of ophthalmic diseases at present. Large-scale Dataset; Color Fundus Photography; Retinal Fundus Image Wu Qiulin Su Yan Hao Yanbin Qi Honggang Pan Chengchang PUBLIC https://creativecommons.org/licenses/by-nc-sa/4.0/ dataset Science Data Bank