A new method for robust contour tracking in cardiac image sequences
Shoujun Zhou, Liang-bin, Wufan Chen · 2005
For the segmentation and robust tracking of the cardiac image sequences (CIS) of magnetic resonance (MR), an optimized algorithm is presented in this paper, which is based on the active contour framework. To use the active contours model (ACM) estimating the cardiac motion, a new concept of generalized fuzzy gradient vector flow (GFGVF) is presented and compared with the classical gradient vector flow (GVF). Then a modified ACM is proposed for motion tracking, which is based on two new external forces: one is the GFGVF field; the other is the relativity of optical flow field (OFF) on predictive contour. For robust tracking the outline of interest, a set of motion equations is presented to describe two correlative updating steps. Another, given some prior terms and likelihood one, the motion state of each point can be found by the maximum a posteriori probability (MAP).