Large-scale annotation dataset for cell/tissue segmentation in H&E-stained images : anti-MNDA (myeloid cells)

LICENSE This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC-BY-NC-SA 4.0) For non-commercial use, please use the dataset under CC-BY-NC-SA. If you would like to use the dataset for commercial purposes, please contact us (ishum-prm@m.u-tokyo.ac.jp). A Tar.gz file contains the following files: - HE image file: {antigen}_{celltype}_{slideID}_{posx}_{posy}_HE.png - Mask image file: {antigen}_{celltype}_{slideID}_{posx}_{posy}_mask.png Each image file is 984x984 px. posX and posY are the leftmost position in WSI coordinate. Mask files store binary segmentation mask (background : 0, target : 1) A csv file contains the following information: antigen : Antibodies for this antigen were used to create the segmentation mask. filename: filename of image or mask file. train_val_test : train, validation, or test sample in the paper. Citation If you use this dataset for your research, please cite our paper. Daisuke Komura, Takumi Onoyama, Koki Shinbo, Hiroto Odaka, Minako Hayakawa, Mieko Ochi, Ranny Rahaningrum Herdiantoputri, Haruya Endo, Hiroto Katoh, Tohru Ikeda, Tetsuo Ushiku, Shumpei Ishikawa, Restaining-based annotation for cancer histology segmentation to overcome annotation-related limitations among pathologists, Patterns, Volume 4, Issue 2, 2023, 100688, https://doi.org/10.1016/j.patter.2023.100688