English

MiDeSeC: A Dataset for Mitosis Detection and Segmentation in Breast Cancer Histopathology Images

Image and Video Processing 2025-07-22 v1 Artificial Intelligence Computer Vision and Pattern Recognition

Abstract

The MiDeSeC dataset is created through H&E stained invasive breast carcinoma, no special type (NST) slides of 25 different patients captured at 40x magnification from the Department of Medical Pathology at Ankara University. The slides have been scanned by 3D Histech Panoramic p250 Flash-3 scanner and Olympus BX50 microscope. As several possible mitosis shapes exist, it is crucial to have a large dataset to cover all the cases. Accordingly, a total of 50 regions is selected from glass slides for 25 patients, each of regions with a size of 1024*1024 pixels. There are more than 500 mitoses in total in these 50 regions. Two-thirds of the regions are reserved for training, the other third for testing.

Keywords

Cite

@article{arxiv.2507.14271,
  title  = {MiDeSeC: A Dataset for Mitosis Detection and Segmentation in Breast Cancer Histopathology Images},
  author = {Refik Samet and Nooshin Nemati and Emrah Hancer and Serpil Sak and Bilge Ayca Kirmizi and Zeynep Yildirim},
  journal= {arXiv preprint arXiv:2507.14271},
  year   = {2025}
}