Self-Supervised Learning for Feature Extraction from Glomerular Images and Disease Classification with Minimal Annotations

Deep learning has great potential in digital kidney pathology. However, its effectiveness depends heavily on the availability of extensively labeled datasets, which are often limited due to the specialized knowledge and time required for their creation. This limitation hinders the widespread application of deep learning for the analysis of kidney biopsy images.