Mol* Volumes & Segmentations 2.0 (Mol* VS 2.0) 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).

Unfortunately, the tightly coupled architecture of Mol* VS 2.0 makes it difficult to reuse its core functionality (especially volume and segmentation preprocessing) in other applications. Therefore, the goal of this thesis is to extract these functions of the Mol* VS 2.0 into a separate library and improve the included volume and segmentation processing algorithms.

The particular objectives are:

• Define the API of the library that decouples the preprocessing logic from the server logic and is open to future extensions.
• Implement the core preprocessing functionality of the current Mol* VS 2.0.
• Provide a simple application to test the library's functions.     
• Evaluate the solution on real datasets of various sizes and types provided by CELLIM.