Computer Science Department, 203C New Computer Science Building, Stony Brook University, Stony Brook, NY, 11794, USA.
Biomedical Informatics Department, HSC L3-045, Stony Brook Medicine, Stony Brook University, Stony Brook, NY, 11794, USA.
Sci Data. 2020 Jun 19;7(1):185. doi: 10.1038/s41597-020-0528-1.
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.
细胞核的分布和形态是癌症诊断和研究的重要标志物。尽管细胞核形态学很重要，但缺乏大规模、准确、公开可获取的细胞核分割数据。针对这一问题，我们开发了一种分析流水线，可对来自多种癌症类型的全切片组织图像中的细胞核进行分割，并带有质量控制流程。我们已经在 10 种癌症类型的 5,060 张全切片组织图像中生成了细胞核分割结果。我们工作的一个关键组成部分是，我们执行了多级质量控制流程（全切片组织图像级和图像斑块级），以评估我们的分割结果的质量。图像斑块级质量控制使用了来自 1,356 个采样图像斑块的手动分割地面实况数据。我们在这项工作中发布的数据集包含来自 10 种不同 TCGA 癌症类型的 5,060 张 TCGA 全切片组织图像和 1,356 张来自相同 10 种癌症类型以及另外 4 种癌症类型的手动分割 TCGA 图像斑块的大约 50 亿个经过质量控制的细胞核。
