MoNuSeg challenge organized at Miccai 2018
Please cite the following paper if you use this repository- Kumar, N., Verma, R., Sharma, S., Bhargava, S., Vahadane, A., & Sethi, A. (2017). A dataset and a technique for generalized nuclear segmentation for computational pathology. IEEE transactions on medical imaging, 36(7), 1550-1560
File name | Description |
---|---|
compute_AJI | Compute average AJI across all nuclei for each image |
Ensemble_mask | Combine instance masks of top 5 techniques to get ensemble mask using majority voting |
correct_nd_missing_nuc_count | Count correctly classified nuclei and missing nuclei in each predicted mask of top 5 techniques |
he_to_binary_mask_final | Use H&E stained image along with associated xml file to generate binary and colored mask |