MiDeSeC: A Dataset for Mitosis Detection and Segmentation in Breast Cancer Histopathology Images
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866908456041054208 |
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| author | Samet, Refik Nemati, Nooshin Hancer, Emrah Sak, Serpil Kirmizi, Bilge Ayca Yildirim, Zeynep |
| author_facet | Samet, Refik Nemati, Nooshin Hancer, Emrah Sak, Serpil Kirmizi, Bilge Ayca Yildirim, Zeynep |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2507_14271 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | MiDeSeC: A Dataset for Mitosis Detection and Segmentation in Breast Cancer Histopathology Images Samet, Refik Nemati, Nooshin Hancer, Emrah Sak, Serpil Kirmizi, Bilge Ayca Yildirim, Zeynep Image and Video Processing Artificial Intelligence Computer Vision and Pattern Recognition 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. |
| title | MiDeSeC: A Dataset for Mitosis Detection and Segmentation in Breast Cancer Histopathology Images |
| topic | Image and Video Processing Artificial Intelligence Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2507.14271 |