LAUSR

Retinal images at 570nm and 600nm are simultaneously captured by retinal oximetry. However, there exists misalignment between the two images, which should be adjusted before they are used to analyze hemoglobin oxygen saturation (SO2). Having a robust, accurate and fast registration scheme can ensure accuracy and speed of SO2 calculation. However, the existing retinal image registration methods cannot meet demand for clinical application of retinal oximetry. For example, errors in the vessel segmentation from each image cause corresponding errors in the registration, point matches may become unreliable when the predefined matching cost is corrupted by pathological retinal images. And it is always a time-consuming task. In this paper, we first analyzed the misalignment reason between dual-wavelength images, and concluded that there only exists the rotation and translation deviation between the two images caused by a mounting deviation of CCD cameras. The parameters were only related to system itself. Based on this, we proposed a registration method based on camera calibration that benefits from feature extraction and affine transformation matrix calculation. The parameters obtained by the proposed method were tested on 80 pairs of retinal images of 5 healthy volunteers and the results showed that the proposed method can successfully register the dual-wavelength images. The proposed registration method can significantly improve SO2 calculation speed while ensuring accuracy.