This page is a collection of some of my open-sourced deep learning work’s supplemental materials (i.e., tutorials / code / datasets from papers)
1. Online supplemental material of “Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases”.
The tutorials for each use case are presented below with data:
| Use Case | Blog | Data |
| Nuclei Segmentation | Tutorial | Data (1.5G) |
| Epithelium Segmentation | Tutorial | Data (336M) |
| Tubule Segmentation | Tutorial | Data (90M) |
| Lymphocyte Detection | Tutorial | Data (6.3M) |
| Mitosis Detection | Tutorial | Data (3.3G) |
| Invasive Ductal Carcinoma Identification | Tutorial | Data (1.6G) |
| Lymphoma Sub-type Classification | Tutorial | Data (1.4G) |
Please note that there has been an update to the overall tutorial pipeline, which is discussed in full here.