ArticleScientific data2020
Dataset of segmented nuclei in hematoxylin and eosin stained histopathology images of ten cancer types.
Article in Scientific data, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- SiNuS: A comprehensive dataset for singular nuclei segmentation forData in brief · 2026Article
- NucFuseRank: Dataset Fusion and Performance Ranking for Nuclei Instance Segmentation.Bioengineering (Basel, Switzerland) · 2026Article
- STHELAR, a multi-tissue dataset linking spatial transcriptomics and histology for cell type annotation.Scientific data · 2026Article
- Deep-learning based colorectal cancer pathological analysis with hyperspectral light field microscopy.iScience · 2025Article
- Novel feature-based method for multi-modal biomedical image registration compared to intensity-based technique.Scientific reports · 2025Article
- Tumour nuclear size heterogeneity as a biomarker for post-radiotherapy outcomes in gynecological malignancies.Physics and imaging in radiation oncology · 2025Article
- Nuclei segmentation and classification from histopathology images using federated learning for end-edge platform.PloS one · 2025Article
- Computational pathology: A survey review and the way forward.Journal of pathology informatics · 2024Review
- Nuclei-level prior knowledge constrained multiple instance learning for breast histopathology whole slide image classification.iScience · 2024Article
- Attention De-sparsification Matters: Inducing diversity in digital pathology representation learning.Medical image analysis · 2024Article
- NuInsSeg: A fully annotated dataset for nuclei instance segmentation in H&E-stained histological images.Scientific data · 2024Article
- Preparing Data for Artificial Intelligence in Pathology with Clinical-Grade Performance.Diagnostics (Basel, Switzerland) · 2023Review
- A Large-scale Synthetic Pathological Dataset for Deep Learning-enabled Segmentation of Breast Cancer.Scientific data · 2023Article
- Cross-platform dataset of multiplex fluorescent cellular object image annotations.Scientific data · 2023Article
- Interoperable slide microscopy viewer and annotation tool for imaging data science and computational pathology.Nature communications · 2023Article
- An Open Dataset of Annotated Metaphase Cell Images for Chromosome Identification.Scientific data · 2023Article
- Super-resolution and segmentation deep learning for breast cancer histopathology image analysis.Biomedical optics express · 2023Article
- Deep learning for survival analysis in breast cancer with whole slide image data.Bioinformatics (Oxford, England) · 2022Article
- Inter-species cell detection - datasets on pulmonary hemosiderophages in equine, human and feline specimens.Scientific data · 2022Article
- NuCLS: A scalable crowdsourcing approach and dataset for nucleus classification and segmentation in breast cancer.GigaScience · 2022Article
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Authors and funding
8 authors.
Funding
Abstract
The distribution and appearance of nuclei are essential markers for the diagnosis and study of cancer. Despite the importance of nuclear morphology, there is a lack of large scale, accurate, publicly accessible nucleus segmentation data. To address this, we developed an analysis pipeline that segments nuclei in whole slide tissue images from multiple cancer types with a quality control process. We have generated nucleus segmentation results in 5,060 Whole Slide Tissue images from 10 cancer types in The Cancer Genome Atlas. One key component of our work is that we carried out a multi-level quality control process (WSI-level and image patch-level), to evaluate the quality of our segmentation results. The image patch-level quality control used manual segmentation ground truth data from 1,356 sampled image patches. The datasets we publish in this work consist of roughly 5 billion quality controlled nuclei from more than 5,060 TCGA WSIs from 10 different TCGA cancer types and 1,356 manually segmented TCGA image patches from the same 10 cancer types plus additional 4 cancer types.
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