Fundus disease is a major cause of blindness. Early detection and timely treatment of fundus diseases can be achieved using optical coherence tomography (OCT), which is an effective approach for preventing blindness. Computer-aided diagnostic techniques are gaining attention as they relieve the pressure on physicians to read films. However, researchers studying computer-aided technology cannot access fundus OCT data owing to privacy concerns. To address this issue, in this study, we searched and combed eight free publicly available fundus OCT databases, interpreted the OCT image features of typical fundus diseases, screened 64 papers based on these computer-assisted algorithm data, and categorized the contributions of these studies. To facilitate the clinical application of computer-aided technology in the early diagnosis of fundus diseases, future efforts can be made in three aspects: improving the stability, repeatability, and generalization of high-precision classification for fundus OCT images; improving the segmentation ability for fundus OCT images; and improving the interpretability of computer-aided algorithms.