title: 3D segmentation of the left ventricle combining long- and short-axis MR images.
abstract: OBJECTIVE
  Segmentation of the left ventricle (LV) is required to quantify LV remodeling after myocardial infarction. Therefore spatiotemporal cine MR sequences including long-axis and short-axis images are acquired. In this paper a new segmentation method for fast and robust segmentation of the left ventricle is presented.
  
  
  METHODS
  The new approach considers the position of the mitral valve and the apex as well as the long-axis contours to generate a 3D LV surface model. The segmentation result can be checked and adjusted in the short-axis images. Finally quantitative parameters were extracted.
  
  
  RESULTS
  For evaluation the LV was segmented in eight datasets of the same subject by two medical experts using a contour drawing tool and the new segmentation tool. The results of both methods were compared concerning interaction time and intra- and inter-observer variance. The presented segmentation method proved to be fast. The mean difference and standard deviation of all parameters are decreased. In case of intra-observer comparison e.g. the mean ESV difference is reduced from 8.8% to 0.5%.
  
  
  CONCLUSIONS
  A semi-automatic LV segmentation method has been developed that combines long- and short-axis views. Using the presented approach the intra- and interobserver difference as well as the time for the segmentation process are decreased. So the semi-automatic segmentation using long- and short-axis information proved to be fast and robust for the quantification of LV mass and volume properties.
authors.affiliation: Department of Medical Informatics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. d.saering@uke.uni-hamburg.de
authors.forename: D
authors.initials: D
authors.lastname: Säring
authors.forename: J
authors.initials: J
authors.lastname: Relan
authors.forename: M
authors.initials: M
authors.lastname: Groth
authors.forename: K
authors.initials: K
authors.lastname: Müllerleile
authors.forename: H
authors.initials: H
authors.lastname: Handels
mesh_terms: D006352:Heart Ventricles / Q000503:physiopathology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D019028:Magnetic Resonance Imaging, Cine; D008943:Mitral Valve / Q000503:physiopathology; D009203:Myocardial Infarction / Q000503:physiopathology; D015588:Observer Variation; D020257:Ventricular Remodeling