MCSpatNet

Repository for Multi-Class Cell Detection Using Spatial Context Representation, ICCV 2021

Shahira Abousamra, David Belinsky, John Van Arnam, Felicia Allard, Eric Yee, Rajarsi Gupta, Tahsin Kurc, Dimitris Samaras, Joel Saltz, Chao Chen, Multi-Class Cell Detection Using Spatial Context Representation, ICCV 2021.

Multi-Class Spatial Network (MCSpatNet)

• Environment set up: refer to environment.md.

• Generate ground truth labels: refer to data_preprocessing.md.

• Model training and evaluation: refer to train_and_test.md.

• Pre-processed datasets: available under datasets. Includes:
  CoNSeP dataset:
  S. Graham, Q. D. Vu, S. E. A. Raza, A. Azam, Y-W. Tsang, J. T. Kwak and N. Rajpoot. "HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Images." Medical Image Analysis, Sept. 2019 .(https://warwick.ac.uk/fac/cross_fac/tia/data/hovernet/)
  
  BRCA-M2C dataset:
  The accompanying dataset to our paper:
  S. Abousamra, D. Belinsky, J. V. Arnam, F. Allard, E. Yee, R. Gupta, T. Kurc, D. Samaras, J. Saltz, C. Chen, "Multi-Class Cell Detection Using Spatial Context Representation", ICCV 2021.
  (https://github.com/TopoXLab/Dataset-BRCA-M2C)

• Trained models: available under pretrained_models. Refer to pretrained_models.md.

• Trained models test results: available under pretrained_results.

Citation

@InProceedings{Abousamra_2021_ICCV,
author    = {Abousamra, Shahira and Belinsky, David and Van Arnam, John and Allard, Felicia and Yee, Eric and Gupta, Rajarsi and Kurc, Tahsin and Samaras, Dimitris and Saltz, Joel and Chen, Chao},  
title     = {Multi-Class Cell Detection Using Spatial Context Representation},  
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},  
year      = {2021},  
}