title: Automatic model-based contour detection of left ventricle myocardium from cardiac CT images.
abstract: OBJECTIVE
  For accurate evaluation of myocardial perfusion on computed tomography images, precise identification of the myocardial borders of the left ventricle (LV) is mandatory. In this article, we propose a method to detect the contour of LV myocardium automatically and accurately.
  
  
  METHODS
  Our detection method is based on active shape model. For precise detection, we estimate the pose and shape parameters separately by three steps: LV coordinate system estimation, myocardial shape estimation, and transformation. In LV coordinate system estimation, we detect heart features followed by the entire LV by introducing machine-learning approach. Since the combination of two types feature detection covers the LV variation, such as pose or shape, we can estimate the LV coordinate system robustly. In myocardial shape estimation, we minimize the energy function including pattern error around myocardium with adjustment of pattern model to input image using estimated concentration of contrast dye. Finally, we detect LV myocardial contours in the input images by transforming the estimated myocardial shape using the matrix composed of the vectors calculated by the LV coordinate system estimation.
  
  
  RESULTS
  In our experiments with 211 images from 145 patients, mean myocardial contours point-to-point errors for our method as compared to ground truth were 1.02 mm for LV endocardium and 1.07 mm for LV epicardium. The average computation time was 2.4 s (on a 3.46 GHz processor with 2-multithreading process).
  
  
  CONCLUSIONS
  Our method achieved accurate and fast myocardial contour detection which may be sufficient for myocardial perfusion examination.
authors.affiliation: Multimedia Laboratory, Corporate Research and Development Center, Toshiba Corporation, 1 Komukaitoshiba-cho, Saiwai-ku, Kawasaki, Kanagawa 212-8582, Japan. takamasa.sugiura@toshiba.co.jp
authors.forename: Takamasa
authors.initials: T
authors.lastname: Sugiura
authors.forename: Tomoyuki
authors.initials: T
authors.lastname: Takeguchi
authors.forename: Yukinobu
authors.initials: Y
authors.lastname: Sakata
authors.forename: Shuhei
authors.initials: S
authors.lastname: Nitta
authors.forename: Tomoya
authors.initials: T
authors.lastname: Okazaki
authors.forename: Nobuyuki
authors.initials: N
authors.lastname: Matsumoto
authors.forename: Yasuko
authors.initials: Y
authors.lastname: Fujisawa
mesh_terms: D000465:Algorithms; D006352:Heart Ventricles / Q000000981:diagnostic imaging*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008962:Models, Theoretical; D009206:Myocardium; D014057:Tomography, X-Ray Computed / Q000379:methods*