title: Automated segmentation of myocardial scar in late enhancement MRI using combined intensity and spatial information.
abstract: Accurate assessment of the size and distribution of a myocardial infarction (MI) from late gadolinium enhancement (LGE) MRI is of significant prognostic value for postinfarction patients. In this paper, an automatic MI identification method combining both intensity and spatial information is presented in a clear framework of (i) initialization, (ii) false acceptance removal, and (iii) false rejection removal. The method was validated on LGE MR images of 20 chronic postinfarction patients, using manually traced MI contours from two independent observers as reference. Good agreement was observed between automatic and manual MI identification. Validation results showed that the average Dice indices, which describe the percentage of overlap between two regions, were 0.83 +/- 0.07 and 0.79 +/- 0.08 between the automatic identification and the manual tracing from observer 1 and observer 2, and the errors in estimated infarct percentage were 0.0 +/- 1.9% and 3.8 +/- 4.7% compared with observer 1 and observer 2. The difference between the automatic method and manual tracing is in the order of interobserver variation. In conclusion, the developed automatic method is accurate and robust in MI delineation, providing an objective tool for quantitative assessment of MI in LGE MR imaging.
authors.affiliation: LKEB - Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands. q.tao@lumc.nl
authors.forename: Qian
authors.initials: Q
authors.lastname: Tao
authors.forename: Julien
authors.initials: J
authors.lastname: Milles
authors.forename: Katja
authors.initials: K
authors.lastname: Zeppenfeld
authors.forename: Hildo J
authors.initials: HJ
authors.lastname: Lamb
authors.forename: Jeroen J
authors.initials: JJ
authors.lastname: Bax
authors.forename: Johan H C
authors.initials: JH
authors.lastname: Reiber
authors.forename: Rob J
authors.initials: RJ
authors.lastname: van der Geest
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002921:Cicatrix / Q000209:etiology / Q000473:pathology*; D003287:Contrast Media; D005260:Female; D019786:Gadolinium DTPA; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009203:Myocardial Infarction / Q000150:complications / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D003287:Contrast Media; D019786:Gadolinium DTPA