MoNuSAC grand-challenge organized at ISBI 2020
This repository contains my implementations of the algorithms which MoNuSAC participants could use for data preparation to train their models at ISBI 2020
| File name | Description |
|---|---|
| Cell_counting | Script to count cells (by type) in each image and store in an excel file |
| Binary_mask_generation | Use H&E stained images(.svs) along with associated xml files to generate binary masks of each annotated cell-type |
| n-ary_mask_generation | Use H&E stained images(.svs) along with associated xml files to generate n-ary masks of each annotated cell-type |
| Compute_PQ_metric | Script to compute Panoptic Quality metric for each n-ary mask image, and store image names and respective PQ values in an excel file |