Mol* Volumes & Segmentations (Mol* VS) enables interactive, real-time visualisation of large-scale volumetric data from advanced microscopy and imaging experiments. These visualisations, important for biological research, include detailed segmentations (breaking down 2D/3D images into biologically meaningful regions such as organelles) and associated annotations to enhance biological understanding. Such data is generated by the Core Facility Cellular Imaging (CELLIM) at the Central European Institute of Technology (CEITEC).

To support early-stage exploratory research, collaboration, and educational use, there is a need for a lightweight, web-based tool that allows researchers and students to easily upload, visualise, annotate, and share volumetric and segmentation data without requiring complex setups or dependencies.

Therefore, the goal of this thesis is to design and implement a lightweight web application and supporting backend for the visualisation and annotation of volumetric and segmentation data in Mol*.

The particular objectives are:

• Enable upload, storage, and necessary conversion of files containing volumetric, segmentation, and annotation data.
• Use modern Mol* features for describing and visualisating this data.
• Implement a REST API for programmatic access to datasets and annotations.
• Ensure secure access and data sharing through e-INFRA CZ authentication and share links.
• Deploy the solution using a CI/CD pipeline on the e-INFRA CZ Kubernetes infrastructure.