The number of people with kidney disease worldwide amounted to nearly 700 million in 2017. This number is expected to increase in the coming years unless investments are made in improved diagnostics, new treatment methods and preventive measures. Kidney diagnostics currently use a combination of urine and blood tests and microscopic analysis of kidney tissue (biopsies). The microscopy methods are several decades old and are based on cutting the tissue into thin/ultra-thin sections and visualizing disease morphology on a large and small scale. Light microscopy has been used since the 1880s to visualize stained larger kidney structures. To visualize the smallest filter structures in the kidney, electron microscopy has been used since the 1950s. Since 2015, we have developed new methods that make it possible for the first time to image these ultra-small structures also with light microscopy. We have shown that we can see nanometer-sized filtration structures in three dimensions in whole tissue samples. Our optical pathology enables a fully automated and quantitative description of pathological changes in the kidney on a small and large scale. In this project, our methods are further developed on human tissue for clinical diagnosis of kidney diseases in collaboration with renal clinics and renal pathologists. We will further apply automatic image analysis with deep learning to more quickly, efficiently and easily diagnose kidney diseases with our optical renal pathology method.