Open-source analysis and visualization of segmented vasculature datasets with VesselVio

Area of Science:

• Biology
• Biomedical Engineering
• Computational Biology

Background:

• Vascular networks are crucial in biological systems, with their analysis vital for understanding health and disease.
• Advanced imaging generates large vasculature datasets, but analysis tools are often costly or complex.
• Existing analysis options present barriers due to cost or high learning curves for programming-based software.

Purpose of the Study:

• To introduce VesselVio, an open-source application for analyzing and visualizing pre-binarized vasculature datasets and vascular graphs.
• To provide an accessible alternative to current paid or complex terminal-based analysis software.
• To demonstrate the utility of VesselVio across diverse 2D and 3D imaging modalities.

Main Methods:

• Developed VesselVio as an open-source application.
• Enabled loading of vasculature datasets and graphs with annotations.
• Allowed processing with custom parameters.
• Tested on ground-truth datasets and compared with existing pipelines.

Main Results:

• VesselVio successfully analyzes and visualizes pre-binarized vasculature datasets and vascular graphs.
• The application handles multiple 2D and 3D dataset formats from various imaging modalities.
• Demonstrated utility with annotated mouse whole-brain vasculature volumes.

Conclusions:

• VesselVio offers a user-friendly, open-source solution for vasculature data analysis.
• It lowers the barrier to entry for researchers studying vascular networks.
• Facilitates improved understanding of vascular roles in biological systems and disease states.