Cerebrovascular segmentation for MRA data using level sets

In this paper, we use a level set based segmentation algorithm to extract the vascular tree from Phase Contrast Magnetic Resonance Angiography, "PCMRA". Classification model finds an optimal partition of homogeneous classes with regular interfaces. Regions and their interfaces are represented by level set functions. The algorithm initializes level sets in each image slice using automatic seed initialization and then iteratively, each level set approaches the steady state and contains the vessel or non-vessel area. The results are validated using a phantom that simulates the "PCMRA". The approach is fast and accurate. Results on various cases demonstrate the accuracy of the approach. (C) 2003 Published by Elsevier Science B.V.