A Simple IgA Nephropathy Grading Diagnosis System Based on CNN

• This project aimed to develop a computer-aided system for diagnosing and grading IgA nephropathy using Convolutional Neural Networks (CNN). By leveraging advanced deep learning techniques, the project successfully implemented CNN models to detect, segment, and classify glomeruli with varying degrees of degeneration. This involved analyzing renal pathology images and identifying specific regions of interest associated with IgA nephropathy.

• The results of this project have the potential to enhance the accuracy and efficiency of diagnosing IgA nephropathy, a kidney disease characterized by abnormal deposition of immunoglobulin A in the kidneys. By leveraging CNN and PyTorch, we hope this system offers a promising approach to automate the grading process, aiding healthcare professionals in providing timely and accurate assessments for better patient care.