The MaskRCNN instance segmentation model was developed using Facebook AI reseach's (FAIR) Detectron 2 framework trained on the [PanNuke Dataset] (https://jgamper.github.io/PanNukeDataset)
The folder Pannuke_cocoFormat contains the Pannuke dataset converted to COCO format since it is the expected format of detectron 2, it can be used to train adn do inferance of the MaskRCNN model using the 'PIMA.ipynb' notebook
An example of instance segmentation on panuke validation set:
@misc{wu2019detectron2, author = {Yuxin Wu and Alexander Kirillov and Francisco Massa and Wan-Yen Lo and Ross Girshick}, title = {Detectron2}, howpublished = {\url{https://github.com/facebookresearch/detectron2}}, year = {2019} }
@inproceedings{liu2018path, author = {Shu Liu and Lu Qi and Haifang Qin and Jianping Shi and Jiaya Jia}, title = {Path Aggregation Network for Instance Segmentation}, booktitle = {Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2018} }
@inproceedings{gamper2019pannuke, title={PanNuke: an open pan-cancer histology dataset for nuclei instance segmentation and classification}, author={Gamper, Jevgenij and Koohbanani, Navid Alemi and Benet, Ksenija and Khuram, Ali and Rajpoot, Nasir}, booktitle={European Congress on Digital Pathology}, pages={11--19}, year={2019}, organization={Springer} }