In recent years, the synergistic application of multi-modal imaging technologies has significantly improved the early diagnostic efficacy of diabetic retinopathy (DR). In terms of research progress, optical coherence tomography angiography (OCTA) has quantified microvascular density, the morphology of the foveal avascular zone (FAZ), and fractal dimension (FD), which revealing changes in the complexity of the microvascular network in the early stages of DR; the widespread adoption of ultra-wide-field imaging technology has increased the detection rate of peripheral retinal ischemia to 82%; and artificial intelligence (AI)-driven novel algorithms have achieved expert-level accuracy in image segmentation and grading, and have enabled cross-modal generation from color fundus photography (CFP)to fluorescein angiography (FFA) images. FD, as a quantitative indicator of vascular network complexity, has been shown in recent years to be significantly associated with DR progression and visual prognosis, and its clinical application potential warrants further exploration. The latest research advances in multi-modal imaging technologies in the early DR diagnostic strategies was systematically reviewed.