3D Organoid Segmentation Dataset for High-Content Screening and Biomedical Image Analysis

This dataset contains 3D organoid microscopy volumes and their corresponding ground-truth segmentation masks for biomedical image analysis and high-content screening research. The dataset was developed to support the training, validation, and benchmarking of automated organoid segmentation methods, including deep learning and computer vision approaches. The dataset consists of raw input volumes stored in the Images folder and their corresponding expert-annotated segmentation masks stored in the Masks folder. Each mask volume corresponds directly to an image volume with matching file identifiers. This resource can be used for 3D organoid segmentation, quantitative morphological analysis, phenotypic profiling, high-content screening, and the development of artificial intelligence methods for biomedical imaging.本数据集收录了面向生物医学图像分析与高内涵筛选研究的三维类器官（organoid）显微镜体数据，及其对应的真值（ground truth）分割掩码。本数据集旨在为涵盖深度学习与计算机视觉技术在内的自动化类器官分割方法的训练、验证与基准测试提供支撑。 数据集的原始输入体数据存储于Images文件夹中，对应的专家标注分割掩码则存储于Masks文件夹中。每个掩码体数据均与带有匹配文件标识符的图像体数据一一对应。该数据集可应用于三维类器官分割、定量形态学分析、表型谱分析、高内涵筛选，以及面向生物医学成像的人工智能方法研发。