Three dimensional reconstruction of coronary arteries from two views.
Geometric representation and measurements of localized lumen stenosis of coronary arteries are important considerations in the diagnosis of cardiovascular diseases. This discrete narrowing of the arteries typically impairs blood flow in regions of the heart, and can be present along the entire length of the artery. Three-dimensional (3-D) reconstruction of coronary arterial tree allows clinician to visualize vascular geometry. Three-dimensional representation of tree topology facilitates calculation of hemodynamic measurements to study myocardial infarction and stenosis. The 3-D arterial tree, computed from two views, can provide more information about the tree geometry than individual views. In this paper, a 3-step algorithm for 3-D reconstruction of arterial tree using two standard views is presented. The first step is a multi-resolution segmentation of the coronary vessels followed by medial-axis detection along the entire arterial tree for both views. In the second step, arterial trees from the two views are registered using medial-axis representation at the coarsest resolution level to obtain an initial 3-D reconstruction. This initial reconstruction at the coarsest level is then modified using 3-D geometrical a priori information. In the third step, the modified reconstruction is projected on the next higher-resolution segmented medial-axis representation and an updated reconstruction is obtained at the higher resolution. The process is iterated until the final 3-D reconstruction is obtained at the finest resolution level. Linear programming based constrained optimization method is used for registering two views at the coarse resolution. This is followed by a Tree-Search method for registering detailed branches at higher resolutions. The automated 3-D reconstruction method was evaluated on computer-simulated as well as human angiogram data. Results show that the automated 3-D reconstruction method provided good registration of computer-simulated data. On human angiogram data, the computed 3-D reconstruction matched well with manual registration.
Sarwal
A
A
Lockheed Martin Corp., Denver, CO 80201, USA.
Dhawan
A P
AP
D000465:Algorithms; D015901:Angiography, Digital Subtraction / Q000706:statistics & numerical data*; D003198:Computer Simulation; D017023:Coronary Angiography / Q000706:statistics & numerical data*; D003327:Coronary Disease / Q000000981:diagnostic imaging; D003331:Coronary Vessels / Q000033:anatomy & histology*; D006801:Humans; D008955:Models, Cardiovascular; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012985:Software Design