Diabetic CF-FA registration Keypoints Ground truth

We present a publicly available dataset of keypoints for multimodal retinal image registration using Color Fundus (CF) and Fractional Anisotropy (FA) images. This dataset is derived from the diabetic retinal image dataset [1], consisting of 59 subjects (29 healthy controls and 30 diabetic patients). The CF images are captured in RGB, while FA images, highlighting microvascular structures, are provided in grayscale, both at a resolution of 720 × 576 pixels. For each subject, we manually annotated 6-8 corresponding keypoint pairs between the modalities, enabling precise alignment of retinal structures. Annotations were independently performed by two experts from Vanderbilt University Medical Center, ensuring high-quality landmark identification.[1]. Hajeb Mohammad Alipour, S., Rabbani, H., & Akhlaghi, M. R. (2012). Diabetic retinopathy grading by digital curvelet transform. Computational and mathematical methods in medicine, 2012(1), 761901.本研究公开了一套用于彩色眼底（Color Fundus, CF）与各向异性分数（Fractional Anisotropy, FA）图像多模态视网膜配准的关键点数据集。该数据集源自糖尿病视网膜图像数据集[1]，共纳入59名受试者，其中29名为健康对照者，30名糖尿病患者。CF图像采用RGB格式采集，而用于凸显微血管结构的FA图像则以灰度格式提供，两类图像的分辨率均为720×576像素。针对每名受试者，研究人员手动标注了6至8组跨模态对应关键点对，可实现视网膜结构的精准配准。本次标注工作由范德堡大学医学中心的两名专家独立完成，保障了标志点标注的高质量。[1] Hajeb Mohammad Alipour, S.、Rabbani, H.与Akhlaghi, M. R.（2012）。基于数字曲波变换的糖尿病视网膜病变分级。《医学计算与数学方法》，2012年第1期，761901。