Chetana Krishnan

Chetana Krishnan works on applying deep learning and image segmentation methods to medical imaging problems, especially for kidney disease (autosomal dominant polycystic kidney disease), prostate cancer, and related organs like airways. The work focuses on developing and refining neural network architectures (such as UNet variants and attention-based models) to automatically identify and measure structures like kidneys, cysts, and prostate zones in MRI and CT scans. This research aims to help clinicians more accurately and efficiently analyze medical images for diagnosis and disease tracking.

Publication output was minimal or absent through the mid-2010s to 2020, then grew sharply starting in 2023, with the highest output in 2024-2026, indicating an increasing and recently active publication pace.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026