Measurements of blood vessel wall areas in black-blood MR images using global minimum snake algorithm

In this paper, we propose a novel boundary detection approach for three-dimensional shape modeling. Our method is based on finding surfaces of minimal weighted area in a Riemannian metric. In order to take advantage of intensity information of images, we further integrate this intensity information into the boundary detection algorithm. We apply this algorithm to identify the inner and outer boundaries of the blood vessel wall in magnetic resonance images, and assess its accuracy and reproducibility. Our algorithm is reasonably accurate (about 2% difference in comparison with the manual method) and highly reproducible.