Visage Imaging GmbH, Berlin 12163, Germany.
IEEE Trans Biomed Eng. 2011 Oct;58(10):2816-24. doi: 10.1109/TBME.2011.2159860. Epub 2011 Jun 16.
An algorithm for the real-time registration of a retinal video sequence captured with a scanning digital ophthalmoscope (SDO) to a retinal composite image is presented. This method is designed for a computer-assisted retinal laser photocoagulation system to compensate for retinal motion and hence enhance the accuracy, speed, and patient safety of retinal laser treatments. The procedure combines intensity and feature-based registration techniques. For the registration of an individual frame, the translational frame-to-frame motion between preceding and current frame is detected by normalized cross correlation. Next, vessel points on the current video frame are identified and an initial transformation estimate is constructed from the calculated translation vector and the quadratic registration matrix of the previous frame. The vessel points are then iteratively matched to the segmented vessel centerline of the composite image to refine the initial transformation and register the video frame to the composite image. Criteria for image quality and algorithm convergence are introduced, which assess the exclusion of single frames from the registration process and enable a loss of tracking signal if necessary. The algorithm was successfully applied to ten different video sequences recorded from patients. It revealed an average accuracy of 2.47 ± 2.0 pixels (∼23.2 ± 18.8 μm) for 2764 evaluated video frames and demonstrated that it meets the clinical requirements.
提出了一种用于将扫描数字眼底照相机（SDO）拍摄的视网膜视频序列实时配准到视网膜复合图像的算法。该方法是为计算机辅助视网膜激光凝固系统设计的，以补偿视网膜运动，从而提高视网膜激光治疗的准确性、速度和患者安全性。该过程结合了强度和基于特征的配准技术。对于单个帧的配准，通过归一化互相关检测到前一帧和当前帧之间的平移帧间运动。接下来，识别当前视频帧上的血管点，并根据计算出的平移向量和前一帧的二次配准矩阵构建初始变换估计。然后，血管点被迭代地匹配到复合图像的分割血管中心线，以细化初始变换并将视频帧配准到复合图像。引入了图像质量和算法收敛性的标准，这些标准评估了从配准过程中排除单个帧的情况，并在必要时允许跟踪信号丢失。该算法已成功应用于从患者记录的十个不同视频序列。它显示了 2764 个评估视频帧的平均精度为 2.47 ± 2.0 像素（约 23.2 ± 18.8 μm），并证明它符合临床要求。
