High-quality, publicly available segmentation annotations of image and video datasets are critical for advancing the field of image processing. In particular, annotations of volumetric images of a large number of targets are time-consuming and challenging. In (Melnikova, A., & Matula, P., 2025), we presented the first publicly available full 3D time-lapse segmentation annotations of migrating cells with complex dynamic shapes. Concretely, three distinct humans annotated two sequences of MDA231 human breast carcinoma cells (Fluo-C3DL-MDA231) from the Cell Tracking Challenge (CTC). This paper aims to provide a comprehensive description of the dataset and accompanying experiments that were not included in (Melnikova, A., & Matula, P., 2025) due to limitations in publication space. Namely, we show that the created annotations are consistent with the previously published tracking markers provided by the CTC organizers and the segmentation accuracy measured based on the 2D gold truth of CTC is within the inter-annotator variability margins. We compared the created 3D annotations with automatically created silver truth provided by CTC. We have found the proposed annotations better represent the complexity of the input images. The presented annotations can be used for testing and training cell segmentation, or analyzing 3D shapes of highly dynamic objects.

翻译：高质量、公开可用的图像和视频数据集分割标注对于推动图像处理领域的发展至关重要。特别是，对包含大量目标的体图像进行标注既耗时又具有挑战性。在（Melnikova, A., & Matula, P., 2025）中，我们首次公开提供了具有复杂动态形状的迁移细胞的全三维延时分割标注。具体而言，三名不同的标注者对来自细胞追踪挑战赛（CTC）的两个MDA231人乳腺癌细胞序列（Fluo-C3DL-MDA231）进行了标注。本文旨在全面描述该数据集以及相关的实验，这些内容因发表篇幅限制未包含在（Melnikova, A., & Matula, P., 2025）中。具体来说，我们证明所创建的标注与CTC组织者先前发布的追踪标记具有一致性，并且基于CTC二维金标准测量的分割精度处于标注者间变异性的范围内。我们将创建的三维标注与CTC提供的自动生成的银标准进行了比较。我们发现所提出的标注能更好地表征输入图像的复杂性。所呈现的标注可用于测试和训练细胞分割，或分析高度动态物体的三维形状。