面向婴儿眼底图像配准的高质量公开数据集
COph100: A comprehensive fundus image registration dataset from infants constituting the "RIDIRP" database
- 构建包含491对图像的婴儿眼底配准数据集
- 涵盖不同图像质量，标注了血管分割与关键点
- 适合研究儿童眼科疾病进展与配准算法
视网膜图像配准在眼科诊断与治疗中至关重要。现有公开数据集多聚焦成人高质图像，样本量小且忽略临床挑战。为此，我们推出COph100——一个面向婴儿的综合性眼底图像配准数据集，构成公开的RIDIRP数据库。该数据集包含100只眼睛，每只眼有2至9次检查，共491对精心挑选的图像。我们手动标注了对应的真实图像点，并为每幅图像提供了自动血管分割掩码。通过先进算法评估了图像质量和配准效果。该资源可支持视网膜配准方法的可靠对比，助力婴儿疾病进展分析，深化对儿科眼病的理解。
原文摘要 · Abstract (English)
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, we introduce COph100, a novel and challenging dataset known as the Comprehensive Ophthalmology Retinal Image Registration dataset for infants with a wide range of image quality issues constituting the public "RIDIRP" database. COph100 consists of 100 eyes, each with 2 to 9 examination sessions, amounting to a total of 491 image pairs carefully selected from the publicly available dataset. We manually labeled the corresponding ground truth image points and provided automatic vessel segmentation masks for each image. We have assessed COph100 in terms of image quality and registration outcomes using state-of-the-art algorithms. This resource enables a robust comparison of retinal registration methodologies and aids in the analysis of disease progression in infants, thereby deepening our understanding of pediatric ophthalmic conditions.
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