SUMMARY Segmentation of single cells in microscopy images is one of the major challenges in computational biology. It is the first step of most bioimage analysis tasks, and essential to create training sets for more advanced deep learning approaches. Here, we propose 3D-Cell-Annotator to solve this task using 3D active surfaces together with shape descriptors as prior information in a semi-automated fashion. The software uses the convenient 3D interface of the widely used Medical Imaging Interaction Toolkit (MITK). Results on 3D biological structures (e.g. spheroids, organoids and embryos) show that the precision of the segmentation reaches the level of a human expert. AVAILABILITY AND IMPLEMENTATION 3D-Cell-Annotator is implemented in CUDA/C++ as a patch for the segmentation module of MITK. The 3D-Cell-Annotator enabled MITK distribution can be downloaded at: www.3D-cell-annotator.org. It works under Windows 64-bit systems and recent Linux distributions even on a consumer level laptop with a CUDA-enabled video card using recent NVIDIA drivers. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

中文翻译：

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3D细胞注释器：一种用于3D显微镜图像中单细胞分割的开源有源表面工具。

发明内容在显微镜图像中对单细胞的分割是计算生物学中的主要挑战之一。这是大多数生物图像分析任务的第一步，对于创建更高级的深度学习方法的培训集至关重要。在这里，我们提出了3D单元注释器来解决此任务，它使用3D活动表面以及形状描述符作为先验信息以半自动化的方式进行。该软件使用了广泛使用的医学影像交互工具包（MITK）的便捷3D界面。3D生物学结构（例如球体，类器官和胚胎）的结果表明，分割的精度达到了人类专家的水平。可用性和实现3D单元注释器在CUDA / C ++中实现，作为MITK细分模块的补丁。支持3D-Cell-annotator的MITK分发可从以下网站下载：www.3D-cell-annotator.org。它可以在Windows 64位系统和最新的Linux发行版上运行，甚至可以在使用最新NVIDIA驱动程序的具有启用CUDA的视频卡的消费级笔记本电脑上使用。补充信息补充数据可从Bioinformatics在线获得。