Computational pathology and deep learning for medical image analysis. Building tools for automated tissue and cell-level diagnostics.
Deep learning-based Anti-Nuclear Antibody pattern classification on HEp-2 cell images. Multi-class prediction across 5 ANA patterns with cell-level analysis.
WHO classification browser and differential diagnosis tool for melanocytic neoplasms. Interactive comparison of diagnostic criteria with computational pathology quantification.
Browse the MNIST handwritten digit dataset and train a neural network in real-time with PyTorch on GPU.