Extracting local stretching from left ventricle angiography data

This paper presents a new method for extracting local surface stretching from the left ventricle (LV) cineangiography data. The algorithm is based on Gaussian curvature for surface stretching recovery under more realistic conformal motion assumption. During conformal motion surface stretching can vary over the surface patch. In particular, surface stretching can be approximated using linear or quadratic (or higher order) functions. Then, coefficients of the approximating function can be calculated and surface stretching computed from changes in surface curvature at corresponding points. For example, linear approximation requires three point correspondences (between consecutive time frames) within small surface patch. The authors demonstrate the higher precision of the new approach (as compared to homothetic assumption in the authors' earlier work) on simulated and real data of the left ventricle of the human heart. The data set was provided by Dr. Alistair Young of the University of Auckland, New Zealand, and consists of the tracked locations of eleven bifurcation points of the left coronary artery and the tracked locations of 292 vessel points for one cardiac cycle (60 frames/cycle).