NuSeC: A Dataset for Nuclei Segmentation in Breast Cancer Histopathology Images
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866915398349225984 |
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| author | Samet, Refik Nemati, Nooshin Hancer, Emrah Sak, Serpil Kirmizi, Bilge Ayca |
| author_facet | Samet, Refik Nemati, Nooshin Hancer, Emrah Sak, Serpil Kirmizi, Bilge Ayca |
| contents | The NuSeC dataset is created by selecting 4 images with the size of 1024*1024 pixels from the slides of each patient among 25 patients. Therefore, there are a total of 100 images in the NuSeC dataset. To carry out a consistent comparative analysis between the methods that will be developed using the NuSeC dataset by the researchers in the future, we divide the NuSeC dataset 75% as the training set and 25% as the testing set. In detail, an image is randomly selected from 4 images of each patient among 25 patients to build the testing set, and then the remaining images are reserved for the training set. While the training set includes 75 images with around 30000 nuclei structures, the testing set includes 25 images with around 6000 nuclei structures. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_14272 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | NuSeC: A Dataset for Nuclei Segmentation in Breast Cancer Histopathology Images Samet, Refik Nemati, Nooshin Hancer, Emrah Sak, Serpil Kirmizi, Bilge Ayca Image and Video Processing Artificial Intelligence Computer Vision and Pattern Recognition The NuSeC dataset is created by selecting 4 images with the size of 1024*1024 pixels from the slides of each patient among 25 patients. Therefore, there are a total of 100 images in the NuSeC dataset. To carry out a consistent comparative analysis between the methods that will be developed using the NuSeC dataset by the researchers in the future, we divide the NuSeC dataset 75% as the training set and 25% as the testing set. In detail, an image is randomly selected from 4 images of each patient among 25 patients to build the testing set, and then the remaining images are reserved for the training set. While the training set includes 75 images with around 30000 nuclei structures, the testing set includes 25 images with around 6000 nuclei structures. |
| title | NuSeC: A Dataset for Nuclei Segmentation in Breast Cancer Histopathology Images |
| topic | Image and Video Processing Artificial Intelligence Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2507.14272 |