Applications of Computer Vision, IEEE Workshop on (2002)
Dec. 3, 2002 to Dec. 4, 2002
Alexandra L.N. Wong , Hong Kong University of Science and Technology
Huafeng Liu , Hong Kong University of Science and Technology
Pengcheng Shi , Hong Kong University of Science and Technology
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 sequence are presented, and are compared to results from gradient-only segmentation.
H. Liu, P. Shi and A. L. Wong, "Segmentation of Myocardium Using Velocity Field Constrained Front Propagation," Applications of Computer Vision, IEEE Workshop on(WACV), Orlando, Florida, 2002, pp. 84.