Title :
An automated myocardial segmentation in cardiac MRI
Author :
El Berbari, R. ; Bloch, Isabelle ; Redheuil, Alban ; Angelini, Emma ; Mousseaux, E. ; Frouin, F. ; Herment, A.
Author_Institution :
CNRS UMR 5141, Paris
Abstract :
In this paper we present an automatic approach to segment cardiac magnetic resonance (CMR) images. A preprocessing step that consists in filtering the image using connected operators (area opening and closing filters) is applied in order to homogenize the cavity and solve the problems due to the papillary muscles. Thereby the GVF snake algorithm is applied with one point clicked in the cavity as initialization and an optimized tuning of parameters for the endocardial contour extraction. The epicardial border is then obtained using the endocardium as initialization. The performance of the proposed method was assessed by experimentation on thirty- nine CMR images. A high agreement between manual and automatic contours was obtained with correlation scores of 0.96 for the endocardium and 0.90 for the epicardium. Overlapping percentage, mean and maximum distances between the two contours show a good performance of the method.
Keywords :
biomedical MRI; cardiology; edge detection; feature extraction; filtering theory; image segmentation; medical image processing; muscle; GVF snake algorithm; automated myocardial segmentation; automatic contours; cardiac MRI; endocardial contour extraction; epicardial border; image filtering; image preprocessing step; magnetic resonance images; papillary muscles; Cardiology; Image edge detection; Image segmentation; Magnetic resonance; Magnetic resonance imaging; Magnetic separation; Muscles; Myocardium; Spatial resolution; Ultrasonic imaging; Algorithms; Endocardium; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Pericardium;
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
Print_ISBN :
978-1-4244-0787-3
DOI :
10.1109/IEMBS.2007.4353341