COph100: A comprehensive fundus image registration dataset from infants constituting the “RIDIRP” database
Abstract Retinal image registration is vital for diagnostic therapeutic applications within the field of ophthalmology. Existing public datasets, focusing on adult retinal pathologies with high-quality images, have limited number of image pairs and neglect clinical challenges. To address this gap, w...
Saved in:
Main Authors: | Yan Hu, Mingdao Gong, Zhongxi Qiu, Jiabao Liu, Hongli Shen, Mingzhen Yuan, Xiaoqing Zhang, Heng Li, Hai Lu, Jiang Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
|
Series: | Scientific Data |
Online Access: | https://doi.org/10.1038/s41597-025-04426-w |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Retinal Fundus Image Registration via Vascular Structure Graph Matching
by: Kexin Deng, et al.
Published: (2010-01-01) -
External Validation of Deep Learning Models for Classifying Etiology of Retinal Hemorrhage Using Diverse Fundus Photography Datasets
by: Pooya Khosravi, et al.
Published: (2024-12-01) -
Multimodal Imaging of the Fundus
by: Atsushi Hayashi, et al.
Published: (2013-01-01) -
Digital fundus image quality assessment
by: V. V. Starovoitov, et al.
Published: (2022-01-01) -
FundusNet: A Deep-Learning Approach for Fast Diagnosis of Neurodegenerative and Eye Diseases Using Fundus Images
by: Wenxing Hu, et al.
Published: (2025-01-01)