Coelho Luís Pedro, Shariff Aabid, Murphy Robert F
Lane Center for Computational Biology, Carnegie Mellon University.
Proc IEEE Int Symp Biomed Imaging. 2009;5193098:518-521. doi: 10.1109/ISBI.2009.5193098.
Image segmentation is an essential step in many image analysis pipelines and many algorithms have been proposed to solve this problem. However, they are often evaluated subjectively or based on a small number of examples. To fill this gap, we hand-segmented a set of 97 fluorescence microscopy images (a total of 4009 cells) and objectively evaluated some previously proposed segmentation algorithms.We focus on algorithms appropriate for high-throughput settings, where only minimal user intervention is feasible.The hand-labeled dataset (and all software used to compare methods) is publicly available to enable others to use it as a benchmark for newly proposed algorithms.
图像分割是许多图像分析流程中的关键步骤，人们已经提出了许多算法来解决这个问题。然而，这些算法的评估往往是主观的，或者基于少量示例。为了填补这一空白，我们手工分割了一组97张荧光显微镜图像（共4009个细胞），并对一些先前提出的分割算法进行了客观评估。我们专注于适用于高通量设置的算法，在这种设置下，只进行最少的用户干预是可行的。手工标记的数据集（以及用于比较方法的所有软件）是公开可用的，以便其他人将其用作新提出算法的基准。
