Abstract
Conference Title: 2015 International Conference on Image Processing Theory, Tools and Applications (IPTA) Conference Start Date: 2015, Nov. 10 Conference End Date: 2015, Nov. 13 Conference Location: Orleans, France In this paper, we develop a new semi-automated segmentation method to cancel the chaotic blood flow signal within the left ventricle (LV) in cardiac magnetic resonance (MR) images with parallel imaging. The segmentation is performed using a deformable model driven by a new external energy based on estimated probability density function (pdf) of the MR signal in the LV. The use of noise distribution through the data allows us both to pull the contour towards the myocardium edges and to ensure the smoothness of the curve. Since data for each slice are acquired with the GRAPPA parallel imaging technique, the spatial segmentation is followed by a temporal propagation to improve the convergence in terms of quality and rapidity. Experiments demonstrate that the proposed model provides better results than those obtained from the standard Active Contour, which should facilitate the use of the method for clinical purposes.