WBC Image Dataset 2

This is two datasets of white blood cell (WBC) images used for ¡°Fast and Robust Segmentation of White Blood Cell Images by Self-supervised Learning¡±, which can be used to evaluate cell image segmentation methods. These two datasets are significantly different from each other in terms of the image color, cell shape, background, etc., which can better evaluate the robustness of WBC segmentation approach. The ground truth segmentation results are manually sketched by domain experts, where the nuclei, cytoplasms and background including red blood cells are marked in white, gray and black respectively. We also submitted the segmentation results by our approach, where the whole WBC region are marked in white and the others are marked in black. Dataset 2 consists of one hundred 300¡Á300 color images, which were collected from the CellaVision blog. The cell images are generally purple and may contain many red blood cells around the white blood cells.

本数据集为《基于自监督学习的白细胞图像快速鲁棒分割》（Fast and Robust Segmentation of White Blood Cell Images by Self-supervised Learning）一文所使用的两组白细胞（white blood cell, WBC）图像数据集，可用于评估细胞图像分割方法。
这两个数据集在图像色彩、细胞形态、背景等方面存在显著差异，能够更全面地评估白细胞分割方法的鲁棒性。
该数据集的分割真值标注由领域专家手动绘制：细胞核、细胞质以及包含红细胞在内的背景分别以白色、灰色和黑色进行标记。本团队同时提交了基于所提方法得到的分割结果：整个白细胞区域以白色标记，其余区域以黑色标记。
数据集2包含100张分辨率为300×300的彩色图像，采集自CellaVision博客。此类细胞图像整体色调偏紫，且白细胞周围通常存在大量红细胞。