  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. Data is available at
https://doi.org/10.7937/tcia.2019.4a4dkp9u
