An automated myocardial segmentation in cardiac MRI.
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.
El Berbari
R
R
INSERM U678, UPMC, F-75013 Paris France; GET, ENST TSI Department, CNRS UMR 5141, F-75013 Paris, France. relberba@imed.jussieu.fr
Bloch
I
I
Redheuil
A
A
Angelini
E
E
Mousseaux
E
E
Frouin
F
F
Herment
A
A
D000465:Algorithms; D004699:Endocardium / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010496:Pericardium / Q000000981:diagnostic imaging*; D011859:Radiography