Spontaneous retinal Venous Pulsations (SVP) are rhythmic changes in the caliber of the central retinal vein and are observed in the optic disc region (ODR) of the retina. Its absence is a critical indicator of various ocular or neurological abnormalities. Recent advances in imaging technology have enabled the development of portable smartphone-based devices for observing the retina and assessment of SVPs. However, the quality of smartphone-based retinal videos is often poor due to noise and image jitting, which in return, can severely obstruct the observation of SVPs. In this work, we developed a fully automated retinal video stabilization method that enables the examination of SVPs captured by various mobile devices. Specifically, we first propose an ODR Spatio-Temporal Localization (ODR-STL) module to localize visible ODR and remove noisy and jittering frames. Then, we introduce a Noise-Aware Template Matching (NATM) module to stabilize high-quality video segments at a fixed position in the field of view. After the processing, the SVPs can be easily observed in the stabilized videos, significantly facilitating user observations. Furthermore, our method is cost-effective and has been tested in both subjective and objective evaluations. Both of the evaluations support its effectiveness in facilitating the observation of SVPs. This can improve the timely diagnosis and treatment of associated diseases, making it a valuable tool for eye health professionals.

翻译：自发性视网膜静脉搏动（SVP）是视网膜中央静脉管径的节律性变化，通常见于视盘区域（ODR）。SVP缺失是多种眼科或神经系统异常的关键临床指标。近年来，成像技术的进步推动了便携式智能手机眼底观察设备的发展，使得SVP评估成为可能。然而，基于智能手机的视网膜视频常因噪声与图像抖动导致质量下降，严重阻碍SVP的临床观察。本研究开发了一种全自动视网膜视频稳像方法，可有效支持多种移动设备采集的SVP影像分析。具体而言，我们首先提出视盘区域时空定位模块（ODR-STL），用于定位可见ODR区域并剔除噪声及抖动帧；随后引入噪声感知模板匹配模块（NATM），在视野固定位置处稳定高质量视频片段。经处理后的稳像视频可清晰呈现SVP，显著提升用户观察体验。该方法经济高效，并已通过主观与客观双维度评估验证，证明其能有效促进SVP观察。该技术可提升相关疾病的及时诊断与治疗，为眼科健康专业人员提供重要工具。