Segmentation of Myocardium Using Velocity Field Constrained Front Propagation

We present a velocity-constrained front propagation approach for myocardium segmentation from magnetic resonance intensity image (MRI) and its matching phase contrast velocity (PCV) images. Our curve evolution criterion is dependent on the prior probability distribution of the myocardial boundary and the conditional boundary probability distribution, which is constructed from the MRI intensity gradient, the PCV magnitude, and the local phase coherence of the PCV direction. A two-step boundary finding strategy is employed to facilitate the computation. For the first image frame, a gradient-only fast marching/level set step is used to approach the boundary, and a narrowband is formed around the curve. The initial boundary is then refined using the full information from priors and all three image sources. For the other frames, the resulting contours from the previous frames are used as the initialization contours, and only refinement step is needed. Experiment results from canine MRI...

• Type: Conference
• Year: 2002
• Where: WACV
• Authors: Alexandra L. N. Wong, Huafeng Liu, Pengcheng Shi
• Keywords: Boundary finding Strategy, Computer Vision, Conditional Boundary Probability, Probability Distribution, WACV 2002