Welcome to the CellMap Segmentation Challenge! This competition provides 289 meticulously annotated training volumes from 22 diverse eFIB-SEM datasets, covering over 40 unique organelle classes. Participants will leverage these high-quality annotations to develop AI-driven segmentation models, advancing our understanding of cellular structures across various biological contexts. With these richly detailed datasets, the challenge sets the stage for significant breakthroughs in electron microscopy image analysis and cellular architecture exploration. The data is publicly available on OpenOrganelle with a collection DOI. For detailed instructions on accessing the data, participating in the challenge, and submitting predictions, visit the official GitHub repository.