A semantic segmentation method to analyze retinal vascular parameters of diabetic nephropathy

The study revealed statistically significant differences in RAOD and RALD among the three groups (<i>p</i> < 0.05) with the RAOD and RALD of the macroalbuminuria group and microalbuminuria group being lower than those of the simple diabetes group. Conversely, there were no significant differences in AWT, AWLR and AWCSA among the three groups (<i>p</i> > 0.05). Additionally, the differences in RVOD and RVLD among the three groups were found to be statistically significant (<i>p</i> < 0.05) with the RVOD and RVLD of the simple diabetes group being lower than those of the microalbuminuria group and macroalbuminuria group. No significant differences were observed in VWT and VWL among the groups. Additionally, RVOD and RVLD were weakly associated with UACR (<i>R</i> = 0.247, <i>p</i> = 0.007; <i>R</i> = 0.210, <i>p</i> = 0.021). Full-pixel semantic segmentation method combined with OCT images is a new retinal vascular scanning technology, which can be used as a new method for early diagnosis of diabetic nephropathy. The structural changes of retinal vessels can be used to predict the severity of diabetic nephropathy during the development of diabetic nephropathy.