CIL:28771

One of the principal challenges in counting or segmenting nuclei is dealing with clustered nuclei. To help assess algorithms' performance in this regard, this synthetic image set consists of five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.30 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).

细胞核计数与分割领域的核心挑战之一，在于处理成团聚集的细胞核。为助力评估相关算法的性能，本合成图像数据集共包含五个子集，各子集的细胞核聚集程度依次递增。数据集提供5个子集，每个子集含20张图像。每张图像内含300个目标对象，这些对象存在重叠与聚集现象，重叠概率区间为0.0至0.6；五个子集分别对应编号CIL 27833、27853、28754、28734与28714。本数据集的目标对象重叠概率为0.30。本数据集的图像通过SIMCEP（http://www.cs.tut.fi/sgn/csb/simcep/tool.html）荧光细胞群体图像仿真平台生成（参考文献：Lehmussola等人，《IEEE医学成像汇刊》，2007年；Lehmussola等人，《IEEE会报》，2008年）。前景/背景分割的真值标签以二值图像形式提供，位于TIFF图像栈的第二张图像中。推荐引用格式：本研究使用的合成1（Synthetic 1）数据集来自Broad生物图像基准集（Broad Bioimage Benchmark Collection，www.broad.mit.edu/bbbc），引用信息为Ruusuvuori等人，《第16届欧洲信号处理大会论文集（EUSIPCO-2008）》，2008年。