COph100：构成“RIDIRP”数据库的综合性婴儿眼底图像配准数据集
COph100: A comprehensive fundus image registration dataset from infants constituting the "RIDIRP" database
AI总结：
本文构建包含100只婴儿眼睛、491个图像对的COph100眼底配准数据集，提供真值点与血管掩膜，以评估现有算法并支撑儿童眼病研究。
摘要：
视网膜图像配准对于眼科领域的诊断和治疗应用至关重要。现有公共数据集聚焦于成人视网膜病变且图像质量较高，不仅图像对数量有限，还忽视了临床挑战。为弥补这一空白，我们推出了COph100，这是一个新颖且具有挑战性的数据集，全称为面向婴儿的综合眼科视网膜图像配准数据集，包含广泛的图像质量问题，并构成公共“RIDIRP”数据库。COph100包含100只眼睛，每只眼睛有2至9次检查时段，共计491个图像对，均从公开可用数据集中精心筛选。我们人工标注了对应的真值图像点，并为每张图像提供了自动血管分割掩膜。我们使用最先进的算法从图像质量和配准结果两方面对COph100进行了评估。该资源能够支持对视网膜配准方法进行稳健比较，并有助于分析婴儿疾病进展，从而加深我们对儿童眼科疾病的理解。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
