A novel method for visualization of entire coronary arterial tree.
The complexity of the coronary circulation especially in the deep layers largely evades experimental investigations. Hence, virtual/computational models depicting structure-function relation of the entire coronary vasculature including the deep layer are imperative. In order to interpret such anatomically based models, fast and efficient visualization algorithms are essential. The complexity of such models, which include vessels from the large proximal coronary arteries and veins down to the capillary level (3 orders of magnitude difference in diameter), is a challenging visualization problem since the resulting geometrical representation consists of millions of vessel segments. In this study, a novel method for rendering the entire porcine coronary arterial tree down to the first segments of capillaries interactively is described which employs geometry reduction and occlusion culling techniques. Due to the tree-shaped nature of the vasculature, these techniques exploit the geometrical topology of the object to achieve a faster rendering speed while still handling the full complexity of the data. We found a significant increase in performance combined with a more accurate, gap-less representation of the vessel segments resulting in a more interactive visualization and analysis tool for the entire coronary arterial tree. The proposed techniques can also be applied to similar data structures, such as neuronal trees, airway structures, bile ducts, and other tree-like structures. The utility and future applications of the proposed algorithms are explored.
Wischgoll
Thomas
T
Department of Computer Science and Engineering, Wright State University, Dayton, OH, USA.
Meyer
Joerg
J
Kaimovitz
Benjamin
B
Lanir
Yoram
Y
Kassab
Ghassan S
GS
D000818:Animals; D002196:Capillaries / Q000033:anatomy & histology*; D003196:Computer Graphics; D003198:Computer Simulation; D003331:Coronary Vessels / Q000033:anatomy & histology*; D003626:Data Display; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008953:Models, Anatomic; D008955:Models, Cardiovascular; D013552:Swine; D014584:User-Computer Interface