title: Comparison of Image Processing Techniques for Nonviable Tissue Quantification in Late Gadolinium Enhancement Cardiac Magnetic Resonance Images.
abstract: OBJECTIVE
  The aim of this study was to compare the performance of quantitative methods, either semiautomated or automated, for left ventricular (LV) nonviable tissue analysis from cardiac magnetic resonance late gadolinium enhancement (CMR-LGE) images.
  
  
  METHODS
  The investigated segmentation techniques were: (i) n-standard deviations thresholding; (ii) full width at half maximum thresholding; (iii) Gaussian mixture model classification; and (iv) fuzzy c-means clustering. These algorithms were applied either in each short axis slice (single-slice approach) or globally considering the entire short-axis stack covering the LV (global approach). CMR-LGE images from 20 patients with ischemic cardiomyopathy were retrospectively selected, and results from each technique were assessed against manual tracing.
  
  
  RESULTS
  All methods provided comparable performance in terms of accuracy in scar detection, computation of local transmurality, and high correlation in scar mass compared with the manual technique. In general, no significant difference between single-slice and global approach was noted. The reproducibility of manual and investigated techniques was confirmed in all cases with slightly lower results for the nSD approach.
  
  
  CONCLUSIONS
  Automated techniques resulted in accurate and reproducible evaluation of LV scars from CMR-LGE in ischemic patients with performance similar to the manual technique. Their application could minimize user interaction and computational time, even when compared with semiautomated approaches.
authors.affiliation: *Centro Cardiologico Monzino, IRCCS †Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy.
authors.forename: M Chiara
authors.initials: MC
authors.lastname: Carminati
authors.forename: Cinzia
authors.initials: C
authors.lastname: Boniotti
authors.forename: Laura
authors.initials: L
authors.lastname: Fusini
authors.forename: Daniele
authors.initials: D
authors.lastname: Andreini
authors.forename: Gianluca
authors.initials: G
authors.lastname: Pontone
authors.forename: Mauro
authors.initials: M
authors.lastname: Pepi
authors.forename: Enrico G
authors.initials: EG
authors.lastname: Caiani
mesh_terms: D000368:Aged; D000465:Algorithms; D002921:Cicatrix / Q000000981:diagnostic imaging*; D003287:Contrast Media; D005260:Female; D006352:Heart Ventricles / Q000000981:diagnostic imaging*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008536:Meglumine / Q000031:analogs & derivatives*; D009203:Myocardial Infarction / Q000000981:diagnostic imaging; D009942:Organometallic Compounds; D015203:Reproducibility of Results
chemical_list: D003287:Contrast Media; D009942:Organometallic Compounds; C064572:gadobenic acid; D008536:Meglumine