Gleason Grading of Prostate Cancer

This research focuses on developing deep learning-based methods for automated Gleason grading of prostate cancer using low-resolution histopathology whole slide images. Gleason grading is a critical step in assessing tumor aggressiveness and guiding treatment decisions. However, manual grading is time-consuming and subject to inter-observer variability. By leveraging advanced deep learning techniques, this project aims to provide a fast, consistent, and scalable solution that supports pathologists in clinical decision-making—even when only low-resolution images are available.