Renal Pathology

Renal pathology research focuses on developing automated methods for analyzing kidney tissue images, aiming to improve diagnostic accuracy and efficiency. Current efforts utilize deep learning models, including convolutional neural networks (CNNs) and transformers, to segment various kidney structures (glomeruli, tubules, layers) and lesions, often leveraging multi-scale and multi-site data, as well as cross-species comparisons (e.g., mouse to human). These advancements hold significant promise for accelerating diagnosis, quantifying disease severity, and reducing inter-observer variability in renal pathology, ultimately improving patient care and advancing research in kidney disease.