BCData: A Large-Scale Dataset and Benchmark for Cell Detection and Counting

Breast cancer is a main malignant tumor for women and the incidence is trending to ascend. Detecting positive and negative tumor cells in the immunohistochemically stained sections of breast tissue to compute the Ki-67 index is an essential means to determine the degree of malignancy of breast cancer. However, there are scarcely public datasets about cell detection of Ki-67 stained images. In this paper, we introduce a large-scale Breast tumor Cell Dataset (BCData) for cell detection and counting, which contains 1,338 images with 181,074 annotated cells belonging to two categories, i.e., positive and negative tumor cells. (We state that our dataset can only be used for non-commercial research.) Our dataset varies widely in both the distributing density of tumor cells and the Ki-67 index. We conduct several cell detection and counting methods on this dataset to set the first benchmark. We believe that our dataset will facilitate further research in cell detection and counting fields in clustering, overlapping, and variational stained conditions. Our dataset is available at https://sites.google.com/view/bcdataset