SiNuS: A comprehensive dataset for singular nuclei segmentation for HER2 grading of breast cancer
Md Shakhawat Hossain, Md Sahilur Rahman, Munim Ahmed · 2026
Read SiNuS: A comprehensive dataset for singular nuclei segmentation for HER2 grading of breast cancer by Md Shakhawat Hossain, Md Sahilur Rahman, Munim Ahmed (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13277659.txt.
Description
Md Shakhawat Hossain, Md Sahilur Rahman, and Munim Ahmed release a 2026 dataset for outlining single cell nuclei in breast cancer slides. Grading the HER2 marker, which guides treatment, must use nuclei that sit intact and apart from neighbours. Earlier computer methods relied on private image collections, slowing progress.
Three expert pathologists independently annotated dual-stained tissue images at high magnification. The set holds thirty-nine patches from twenty-one patients, with more than eighteen hundred nuclei under the loose rule and fewer under full consensus. Both inclusive and strict consensus labels are supplied, along with several mask formats. Test runs with deep learning models validated the resource for automated HER2 grading research.
Catalog record
| CREATOR | Md Shakhawat Hossain, Md Sahilur Rahman, Munim Ahmed |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 32 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |