Blood Vessel Segmentation from Volume Data

In this research, we propose a new robust segmentation method for blood vessels from volume data. The proposed method extracts a blood vessel with detailed geometry, such as bifurcations and changes in radius. In addition, it can generate an abstract tree data structure representing the extracted blood vessel. Thus, the resulting data is very useful for various geometric operations and visualization in many 3D medical applications, including surgical simulation.

 

 

Participants: Kwang-Man Oh, James K. Hahn