Color fundus photograph registration based on feature and intensity for longitudinal evaluation of diabetic retinopathy progression

Abstract

Longitudinal disease progression evaluation between follow-up examinations relies on precise registration of medical images. Compared to other medical imaging methods, color fundus photograph, a common retinal examination, is easily affected by eye movements while shooting, for which we think it is necessary to develop a reliable longitudinal registration method for this modality. Thus, the purpose of this study was to propose a robust registration method for longitudinal color fundus photographs and establish a longitudinal retinal registration dataset. In the proposed algorithm, radiation-variation insensitive feature transform (RIFT) feature points were calculated and aligned, followed by further refinement using a normalized total gradient (NTG). Experiments and ablation analyses were conducted on both public and private datasets, using the mean registration error and registration success plot as the main evaluation metrics. The results showed that our proposed method was comparable to other state-of-the-art registration algorithms and was particularly accurate for longitudinal images with disease progression. We believe the proposed method will be beneficial for the longitudinal evaluation of fundus images.