CoCryoViS: Collaborative online cryo-electron tomography visualization system

We present a collaborative, interactive, web-based visualization and processing system for Cryo-Electron Tomography (cryo-ET) data that supports the complete workflow, from raw tilt-series projections to final 3D segmentations. The system integrates tilt-series alignment, motion correction, tomographic reconstruction, manual and pseudo-annotation, deep model training, inference, and visualization, all accessible through a unified web-based interface. The backend manages computationally intensive tasks, including advanced tomographic reconstruction, pseudo-annotation generation, deep learning model training, and large-scale segmentation of new datasets. It features separate queues for CPU and GPU tasks, allowing users to prepare and manage large workloads in advance. The frontend supports lightweight tomographic reconstruction, manual data annotation, segmentation with pretrained models, interactive exploration of pipeline stages, and real-time monitoring of queued tasks. Key processing steps are available on both the client and server sides, providing flexibility for diverse computational environments, enabling visualization of externally hosted datasets, and supporting data privacy when required. The system is designed for collaborative workflows, enabling multiple users to share input data, annotations, and trained models within joint projects. Its modular architecture allows easy extension with additional stages on either the client or server side, making it adaptable to specialized pipelines within individual institutions. We demonstrate the system's capabilities on representative cryo-ET datasets, highlighting its utility for both individual researchers and distributed teams working on structural analysis of complex cellular environments. The initial release of the system is available at https://cocryovis.lgm.fri.uni-lj.si/ (Project repository: https://github.com/nanovis/cocryovis, mirror deploy: https://tomography.kaust.edu.sa/), and the entire system will become open source so that any visualization or domain researcher can further enhance its functionality.